THE AFFORDABILITY OF HOUSING IN ONTARIO - CFAA · PDF fileThe Affordability of Housing in...

THE AFFORDABILITY OF HOUSING IN ONTARIO: TRENDS, CAUSES, SOLUTIONS*

January 13, 2005 Vincent Brescia†

* The author would like to thank the contribution of the FRPO Affordable Housing Committee, especially Lawrence B. Smith and John Dickie. All errors are the responsibility of the author. † Vincent Brescia is President and CEO of the Federation of Rental-housing Providers of Ontario (FRPO), a non-profit industry association for residential rental property owners and managers. He has previously worked in numerous capacities as a housing and government policy analyst, including at CMHC, Clayton Research Associates Ltd, Ontario Ministry of Housing, Ontario Ministry of Finance, Management Board of Cabinet, the Greater Toronto Home Builders’ Association, and the Universal Workers Union, Local 183.

The Affordability of Housing in Ontario

i

ABSTRACT This paper has examined trends in the affordability of housing in Ontario over the past 20 to 40 years, and the primary factors influencing these trends, including a detailed review of trends in the two variables used in housing affordability indicators: household incomes and housing costs. Traditional shelter cost to household income ratios show that a growing portion of households have been spending more than 50 percent of their income in rent since 1981. However, these traditional measures do not account for household formation, changing household types, the changing quality of housing or changing consumption patterns. Adjusting for any of these changes reveals that housing has been becoming more and more affordable in Ontario. In fact, real income growth in all income quintiles has allowed more and more people to form an independent household over time, and allowed them to improve the size and quality of the housing they are living in, and increased their per capita disposable income after housing costs. The research also shows that housing affordability is primarily an income issue. Changes in housing affordability over time essentially mirror the pattern of changes in incomes. The most obvious solution to an income based affordability problem would be income supports, and a housing allowance is demonstrated to be the most cost effective approach. Housing costs have been increasing in real terms since 1981, but when adjusted for changes in quality, they have actually been flat or declined. The research indicates that the primary factor influencing changes in the cost of housing over time has been changes in the price of land. A growing body of empirical work is finding that government barriers to housing supply, at any price range, are the primary causes of housing affordability problem in many jurisdictions, because the market’s natural filtering process becomes asphyxiated. Therefore, the most important thing that the province can do to reduce housing costs is to remove impediments to supply of housing, regardless of the price range at which the new housing is supplied. Land supply and zoning restrictions should be given particular attention.


ii

EXECUTIVE SUMMARY This paper has reviewed in some detail the trends in housing affordability in Ontario over the past 20-40 years, and attempted to identify the major factors influencing these trends. Understanding the key causes of affordability problems will better allow the government to make the appropriate response to address the problem. The main findings of the paper are briefly summarized below.

Affordability • The percentage of Ontario’s population spending more than 50 percent of their

income on housing costs increased from 8.1 percent in 1981 to 10.6 percent in 2001 • This trend was experienced by both homeowners and renters • However, this fixed shelter to income ratio is demonstrated to give an inaccurate

indication of trends in the affordability of housing, because it does not take into account the impact of changing household types and sizes, household formation and housing consumption patterns

• When affordability indicators are adjusted to factor in the above, it is demonstrated that housing affordability problems have actually lessened since 1981: affordability worsened between 1981 and 1996, but improved dramatically between 1996 and 2001

• It is demonstrated that housing affordability problems are really income problems, not housing problems, and that housing affordability trends are driven by income trends

Trends In Incomes • Average real incomes have been increasing in Ontario. The average family’s real

income increased by $13,000 between 1981 and 2001 • Average real incomes increased for both tenants and owners over the period • The rate of real family income growth in the bottom income quintile largely matched

that of all families until 1996, when there was sharp drop in the income of the lowest quintile households; however, since then, real income growth of lowest quintile families has outpaced that of all families

• The incidence of low income increased substantially during the early 1990s, but has been on a downward trend since 1996

• Two demographic trends have had a significant impact on incomes: o the incomes of recent immigrants has been declining compared to their

predecessors from the 1960s and 1970s o the incomes of young households has declined in a similar fashion

Housing Costs • Real monthly housing costs rose for both owners and renters in the 1980s, and remain

higher today than in the early 1980s • However, housing size and quality has also been increasing • Quality adjusted housing costs have actually been relatively flat • The major factor behind changes in housing costs has been changes in the cost of

land: real land costs increased significantly in the 1970s and 1980s


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• A wide array of academic evidence is reviewed which conclusively demonstrates that barriers to housing supply (land supply, density, zoning, etc.), at any price range, are a major cause of high housing costs and housing affordability problems

Changing Housing Consumption Patterns • Ontarians have been increasing their consumption of housing: they now have bigger

homes, with more amenities • At the same time, there are fewer people in these homes: household size is shrinking

and single person households have grown dramatically • These trends make housing more costly on a per-person basis, and on a per household

basis, particularly the growing number of single person households • This is the good news about increasing housing cost-to-income ratios: increasing

housing consumption and quality • Rising incomes have also resulted in increased household formation. Although their

circumstances are improving, this shows up in affordability indicators as a growing problem, revealing a flaw with traditional affordability indicators.

Conclusion Given the findings, government actions to address affordable housing concerns should be focused on addressing the main areas influencing trends in housing affordability:

1) Income Distribution 2) Land/Housing Supply

Program Responses The program responses which will most cost effectively reduce the incidence of affordable housing problems follow from the main findings of the paper. These program responses can be categorized into four main areas:

1) Income supplements: the paper shows that shelter allowances are by far the most cost effective way to address the housing affordability

2) Remove barriers to housing supply: example policies might include: strong provincial policies which promote an adequate supply of land; strong provincial oversight of those policies; and independent review of the local development approvals process to ensure provincial land supply objectives are met. Also, rent controls should be eliminated because they actually choke off the supply of relatively low cost housing for low-income households in several ways.

3) Eliminate unfair property taxes: the multi-residential property tax in many urban centres in Ontario is grossly regressive, and may be the primary cause of housing affordability problems for tens of thousands of low income households.

4) Government sponsored special needs construction: the government should focus its activities in the area of new construction to programs which provide incentives for the development of housing with physical characteristics not being supplied by the marketplace, such as disabled access housing.


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TABLE OF CONTENTS EXECUTIVE SUMMARY ................................................................................................ ii TABLE OF CONTENTS................................................................................................... iv INTRODUCTION .............................................................................................................. 1 TRENDS IN HOUSING AFFORDABILITY.................................................................... 2

Characteristics of Households in Core Need .................................................................. 3 TRENDS IN INCOMES..................................................................................................... 6

Income Trends by Tenure ............................................................................................... 7 Housing Is An Income Issue ........................................................................................... 7

EXPLAINING THE TRENDS IN INCOMES................................................................... 9 Tenant Household Income a Residual: Declining Percentage of Renters ...................... 9 Household Formation.................................................................................................... 10 Drop in Income of Young Workers .............................................................................. 13 Immigration................................................................................................................... 13 Ageing Population ........................................................................................................ 14

TRENDS IN HOUSING COSTS ..................................................................................... 16 Local Trends ................................................................................................................. 17

EXPLAINING THE TRENDS IN HOUSING COSTS ................................................... 18 Are Construction Costs Behind the Changes in Housing Costs? ................................. 18 Are Housing Quality Changes Behind the Changes in Housing Costs?....................... 19 Are Housing Size Changes Behind the Change in Housing Costs? ............................. 22 Is The Tenant Protection Act (1998) Responsible for Increasing Rents?..................... 23

FILTERING AND AFFORDABLE HOUSING.............................................................. 25 Empirical Studies of Filtering....................................................................................... 25 Vacancy Chain Studies ................................................................................................. 26 FRPO Filtering Study ................................................................................................... 27 Why Filtering Is Important?.......................................................................................... 28

GOVERNMENT REGULATORY BARRIERS AND AFFORDABLE HOUSING...... 29 Land Regulation and Zoning ........................................................................................ 29 Rent Controls as a Supply Barrier ................................................................................ 30 Rent Controls and the Unregulated Market .................................................................. 32 Rent Controls and Filtering........................................................................................... 33 Property Tax Policies.................................................................................................... 35

APPROPRIATE GOVERNMENT RESPONSES ........................................................... 36 Government Sponsored New “Affordable Housing” Construction Program............... 36 Housing (Shelter) Allowances ...................................................................................... 39 Rent Supplements ......................................................................................................... 43 Immigration Support..................................................................................................... 43 Special Needs Housing ................................................................................................. 44 Reductions In Government Barriers To Supply............................................................ 44 Property Tax Reform .................................................................................................... 45 Affordability Indicators and Thresholds....................................................................... 46

BIBLIOGRAPHY............................................................................................................. 48 APPENDIX A: IMMIGRATION TO ONTARIO REFLECTS NATIONAL TREND ... 54

INTRODUCTION Public concerns about affordability arise from the fact that housing represents a large portion of the budgets of most low income households. Devoting a large portion of income to housing raises concerns beyond housing - beyond just ensuring that everyone has a decent home. A significant and related concern is about the non-housing or "after housing" consumption of these households - the funds they have available, after paying for their housing, for food, clothing and other necessities. Both concerns have implications for the household's wellbeing, and in some cases, the household's ability to remain housed. However, the concept of housing affordability is problematic. This one term encompasses all of the following issues:

o The distribution of housing prices o The distribution housing quality o The distribution of income o Short-term income changes versus permanent income (long-term income) o The ability of households to borrow o Public policies affecting housing markets o Conditions affecting supply and demand o Housing consumption choices and preferences of households

The concept affordability therefore encompasses a wide array of potential government policies and programs. This paper will attempt to look at all of the various factors influencing the affordability of housing, so we can best evaluate which government policies will be most affective in addressing the issue. It will also review the appropriateness of current housing affordability as indicators of trends in the affordability of housing, to see whether simple shelter to income ratios and thresholds are appropriate in giving policy makers and the general public a proper understanding of changing housing and social conditions.


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TRENDS IN HOUSING AFFORDABILITY We begin by reviewing the standard housing affordability indicators used now in Canada and Ontario: shelter cost to household income ratios. Over the past 25 years, there has been a general trend upwards in the number of Ontario households spending more than 50 percent of their income on housing costs. Between 1981 and 2001, the percentage of the population paying more than 50 percent of income increased from 8.1 percent to 10.6 percent. The total number of households spending more than 50 percent increased from 239,000 in 1981, to 441,000 in 2001.

Percent of Households Paying More Than 50% of Income on Housing Costs, Ontario

0

2

4

6

8

10

12

14

1981 1986 1991 1996 2001

Source: Statistics Canada Census, various years

Renter Households Paying More Than 50% of Income in Rent, Ontario

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

1981 1986 1991 1996 2001


Owner Households Paying More Than 50% of Income on Housing Costs, Ontario

020,00040,00060,00080,000

100,000120,000140,000160,000180,000

1981 1986 1991 1996 2001Source: Statistics Canada Census, various years

This trend has included both homeowners and renters. The number of homeowners spending more than 50 percent of their income on housing costs increased from 95,000 to 175,000 over this same period. This represent an 85 percent increase in the number of owners households spending more than 50 percent of income in housing costs. Similarly, the number of renter households spending more than 50 percent of their income in rent increased from 144,000 in 1981 to 266,000 in 2001, an 84 percent increase. In both 1981 and 2001, renter households accounted for about 60 percent of households spending more than 50 percent of income on housing costs. Altogether, about 20 percent of renters, and six percent of homeowners paid more than 50 percent of their incomes on housing costs in 2001. As discussed earlier, these are crude measures of housing affordability problems. Such measures do not account for:


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o The distribution of housing prices o The distribution housing quality o The distribution of income o Short-term income changes versus permanent income (long-term income) o The ability of households to borrow o Public policies affecting housing markets o Conditions affecting supply and demand o Housing consumption choices and preferences of households

The measure is also problematic because it measures current housing costs against last year’s income. Therefore, it is not an accurate reflection of housing affordability problems, because the income and housing variables are from two different time periods. It also does not account for non-income wealth which means many households who really to not have a housing affordability problem get included, particularly seniors who have accumulated wealth but may have low incomes. As a result, the measure is biased towards over-reporting of housing affordability problems, because an individual household’s income typically rises over time. Some of these issues are explored further, to determine whether or not these issues impact on the ultimate accuracy or usefulness of current housing affordability indicators.

Characteristics of Households in Core Need Canada Mortgage and Housing Corporation (CMHC) has developed a somewhat more sophisticated shelter cost to income ratio measure of housing affordability problems which is called core need. Someone is considered to be in core need if they spend more than 30 percent of their income in order to obtain suitable or adequate housing. The core need calculations filter out those who have higher incomes, who are presumably making a conscious choice to spend a large portion of their income in rent, and those who are spending large amounts on housing, as this also reflects a conscious decision to spend above average amounts on housing. By and large, trends in the more crude indicators reviewed above are generally mirrored in the core need numbers. The chart below shows the general household makeup of those in core need in Ontario in 2001. The data shows that seniors make up 31 percent of Ontario’s 674,000 households in core need. As we will see later in this paper, a good portion of these households may not actually have a serious housing problem. This is because their low incomes reflect their retirement status rather than material poverty. Many of these households may in fact have significant assets. Given the longer life expectancy of women generally, it is not surprising to find that female one person households represent 58 percent of senior households in need.


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The next most common type of household in core need is couples with children at 17 percent. Lone parent families also represent 17 percent of those in core need.

Core Need Households by Type Ontario, 2001 (Non-Native)

Seniors31%

Lone Parents

2%

Couples No Children

6%Female 1 person

12%Male

1 person11%

Famale One Person

18%

Female lone

parent15%

multiple family1%

male lone parent2%

Male 1 Person

5%

Couples nochild 8%

Couples with children

17%

Other1%

2+ persons2%

Source: CMHC.

Altogether, 45 percent of those in core need are single person households. These households represent a growing portion of Ontario’s households. Given that the same 30 percent affordability threshold is used for all households in need, regardless of household size, it is not surprising to find many singles in this category. Students would be included in this category. It may be that a good portion of these households can live comfortably with housing taking up more than 30 percent of their income. By contrast, two person households are rarely in core need, perhaps demonstrating the cost effectiveness of sharing housing costs. The number of core need households in Ontario increased significantly by 1996, and have declined modestly since 1996. According to CMHC (2004), the percentage of households in core need in Ontario increased from 12 percent of the population in 1991, to 19 percent in 1996, and subsequently declined to 17 percent in 2001. It is one of the great ironies of the Canadian public discourse on housing policy that the people who do not have a housing problem are identified as having a housing problem. The vast majority of those in core need have suitable and adequate housing. They do not have a housing problem. Their problem is actually that their income is too low to afford even very low cost housing. According to the federal government’s most recent core need study: “the overwhelming reason that households are in core need is that they spend 30 percent or more of their income in shelter and do not have enough income to access acceptable housing.” The average core need renter household in Ontario in 2001 had an income of $19,682. This means they can only afford a rent of $492 per month based on a 30 percent standard. The rent they are currently paying was, on average, $708, compared to CMHC’s Ontario average rent of $815, so their housing was relatively low in cost.


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A small portion of those in core need actually have an identifiable problem with their housing. As the chart right demonstrates, 92 percent of those in core need have an affordability problem. About 11 percent have a suitability problem (overcrowded), and 13 percent an adequacy problem. However, even here their problem may have more to do with their income than anything else. Their low incomes likely mean that they cannot access suitable and adequate housing. It is very likely that most of these households could find suitable and adequate housing if they received an income supplement.

Core Need Problem Type of Problem, Canada CMAs, 2001

0%10%20%30%40%50%60%70%80%90%

100%

Affordability Adequacy SuitabilitySource: CMHC.

In the next two sections, we take a look at trends in the two variables which make up standard housing affordability ratios: trends in incomes and trends in housing costs.


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TRENDS IN INCOMES Incomes have been improving in Ontario over the past 25 years. Average real incomes have risen from about $55,000 in 1981 in constant $2002 (this means the average has been adjusted for inflation), to about $68,000 in 2002, an increase of $13,000. This represents a real increase in purchasing power of 24 percent over the period. Those in the lowest income quintile have also experienced income growth, but at a slower rate. Their incomes increased by $2,400 between 1981 and 2002, from $13,300 to $15,700. This represents in increase of 18 percent over this period, showing a slower rate of growth than the overall average for all families. The distribution of income growth has not been even. From 1981 to 1995, the growth rates in incomes for the lowest quintile largely matched the overall average. The sudden change in 1996 likely reflects the 22 percent reduction in welfare benefits in Ontario. Families on welfare are likely a very high percentage of families in the lowest quintile1. Since 1996, income growth has been faster for the lowest quintile: lowest quintile incomes grew by 22 percent between 1996 and 2003, versus 16 percent for the overall population.

Average Family Income, Ontario, Constant $2002

$50,000$52,000$54,000$56,000$58,000$60,000$62,000$64,000$66,000$68,000$70,000

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

All

Hou

seho

lds

$12,000$12,500$13,000$13,500$14,000$14,500$15,000$15,500$16,000$16,500$17,000

Low

est Q

uint

ile

All Households Lowest Quntile

Source: FRPO based on Statistics Canada Data.

Looking at incidence of low-income2 in Ontario confirms significant changes to the incidence of low income through the past 25 years. The number of persons in Ontario with low income increased from 1.2 million in 1980 to 1.8 million in 1996. Using an average household size of 2.7, that would be an increase of 222,000 households. Since 1996, the number has been on a general downward trend. In contrast with non-seniors, the incidence of low income in seniors is stable and declining. This reflects the fact that many seniors have a stable source of income, and the fact that government transfers to seniors are quite high. Elderly families received an estimated $20,200, on average, in government transfers in 2002, compared to an average $5,300 for non-elderly families (Statistics Canada, 2002).

Persons In Low Income by Age Ontario, 1980-2002, (000)

0200400600800

100012001400160018002000

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

65+ < 18 18-64Source: Statistics Canada.

1 Statistics Canada (2002) shows that the majority of families that have no income earner are in low income. We can expect this to include a high percentage of families on welfare. 2 Statistics Canada defines someone to be in low-income if their income, adjusted for family size and composition, is less than 50 percent of the median for an equivalent family.


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The chart opposite compares the incidence of low income with our first affordability indicator – the number of households spending more than 50 percent of their income in rent. Here we see that the pattern in incidence of low income closely matches trends in housing affordability: it appears that changing income patterns provide significant explanation for changes in housing affordability indicators.

50%+ STIR Households and Low Income Households, Ontario

0

2

4

6

8

10

12

14

1981 1986 1991 1996 2001

Per

cent

of P

opul

atio

n

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

(000

)

50% STIR

Low Income

Source: Statistics Canada and Census, various years

Income Trends by Tenure A look at income changes by tenure reveal some differences in the income growth patterns of owners versus tenants. Owners in Ontario, on average, experienced real income growth of about $20,000 (in constant $2001) between 1981 and 2001. This represents real income growth of about 33 percent. Homeowner incomes fell slightly between 1991 and 1996, but subsequently showed significant growth.

Average Renter Household Income,

Ontario, Constant $2001

$0$5,000

$10,000$15,000$20,000$25,000$30,000$35,000$40,000$45,000

1981 1986 1991 1996 2001


Average Owner Household Income, Ontario, Constant $2001

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

1981 1986 1991 1996 2001


Renter households have also experienced income growth. The average tenant’s real income increased from $35,000 in 1981 to about $41,000 in 1991. As would be expected, given our findings above and knowing that low income households dominate the rental tenure, real tenant incomes dropped significantly in the mid 1990s, but have since recovered. Tenants average real incomes are about 14 percent higher than they were in 1980s, demonstrating a slower income growth rate for tenants than homeowners.

Housing Is An Income Issue Our research above revealed a high correlation with changes in the income distribution with changes in housing affordability indicators. Lefebvre (2000) reaffirms these findings. She documents in detail the housing conditions in Canada by income quintile, and compares and contrasts conditions amongst quintiles. She finds that the vast majority


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of households are suitably housed – that is, their houses did not need major repairs and were big enough for their needs. However, she finds that households with low incomes were 50 percent more likely to be in unsuitable housing, and spent almost twice the proportion of income on rent as those in the top quintile. She concludes that housing is primarily an income issue. Therefore, we shall examine the key factors influencing trends in incomes in Ontario.


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EXPLAINING THE TRENDS IN INCOMES Several factors have been influencing the trends in the incomes we use to calculate housing affordability indicators. The following factors are examined in more detail: • Tenant household incomes as a residual in the overall income distribution • Household formation implications for tenant household income • Changing income patterns for young workers and immigrants • Impact of the ageing of the renter population

Tenant Household Income a Residual: Declining Percentage of Renters Affordability discussions often focus on tenants. One reason tenants’ income growth might have been slower than homeowners’ recently is the growing rate of home ownership. As higher income renters leave for homeownership, they leave behind a lower average income amongst remaining renters. With a higher proportion of the population opting for home ownership, we would expect the average income of the remaining tenants to be lower, other things being equal. Moreover, new renter households tend to have lower income on average, since they rent when they are just able to afford it. Also, if people are moving more quickly into homeownership, their early years of ownership are likely to be characterised by high housing cost to income ratios, which may partly explain why we are seeing an increase in cost-to-income ratios for owners as well.

Percentage of Households Who Are Renters, Ontario

29%

30%

31%

32%

33%

34%

35%

36%

37%


One way to check this would be to look at rents compared to all household income. By comparing rents to the full distribution of household income, we get a better sense of changes in housing affordability conditions for society as a whole. Here we see that rents in Ontario have been declining as a percentage of average household income. For the average household in Ontario, affordability conditions have been improving. This supports the notion of rental housing incomes being a residual.

Average Rent as a Percent of Average Household Income, Ont.

12.5

13

13.5

14

14.5

15

15.5

1981 1986 1991 1996 2001Source: Census, various years.

We might also be interested in comparing lowest quintile incomes with lowest quintile rents. Since we do not have the latter, a comparison of lowest quintile incomes with


9

average rents is reproduced opposite. If we assume the distribution of housing costs remain consistent, we may use this to determine trends in affordability, but not level of affordability3. Here we see a different picture. There was a rapid deterioration in the affordability of average rents for the lowest quintile family between 1981 and 1996, and then a dramatic improvement in the 1996-2001 period. Therefore, for the period 1981 to 2001, there appears to be no significant change in the affordability of housing for low income households as a result of the dramatic improvement in affordability conditions since 1996.

Average Gross Rent Vs. Lowest Quintile Family Income, Ontario

52

5456

1981 1986 1991 1996 2001Source: FRPO based on Census and Statistics Canada data.

5860

6264

66

6870

Perc

ent

Household Formation As mentioned earlier, housing affordability indicators have some significant conceptual problems. This is apparent when we look at the impact of household formation on household incomes. Incomes have been improving for all types of households in Canada and Ontario. From Statistics Canada data we know that with the exception of non-earner married couples and non-earner non-elderly females, real incomes have increased for every type of family in Canada since 1980. For example, the chart opposite demonstrates average total income4 for unattached individuals in Ontario. Here we see that there has been considerable real income growth, particularly since 1996.

Average Market Income for Unattached Individuals, Ontario

$25,000

$27,000

$29,000

$31,000

$33,000

$35,000

$37,000

$39,000

$41,000

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Unattached individuals Non-elderly males Non-elderly females

Source: Statistics Canada, CANSIM, table 202-0202.

3 This is because the use of average rents distorts the rent to income ratio. We know from Census data that lower income households occupy housing in the low end of the housing cost distribution. A better indicator would use lowest quintile rents, but these are not readily available. If the distribution of housing costs retains a relatively consistent shape, this will provide a useful trend indicator. 4 Total income is the sum of market income and government transfers.


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As incomes improve over time, more and more people are able to form their own household, whereas previously they may have been prevented from doing so by an inadequate income. Having their own home becomes more achievable – more affordable. At the chart opposite shows, rents as a percentage of average per capita income in Ontario have been steadily declining. Average gross rent represented 43 percent of per capita income in Ontario in 1981, but dropped to 37 percent in 2001. This change represents a significant trend toward improvement in the affordability of rental housing.

Average Gross Rent Percent of Average Per Capita Income

Ontario

34

3536

3738

3940

4142

43


This is clearly the case with single person households who have grown from 7 percent of the population in Canada in 1951 to 26 percent in 2001. The same trend holds for Ontario. This is a large expansion in household formation. Rising incomes have meant that housing has become affordable for many households who previously could not afford to form their own separate household. However, because they are single income households, and because these households have just marginally passed a threshold that allows them to afford their housing, they will register in housing affordability data as having low incomes, and has having a housing affordability problem.

Single Person Households as a Percent of All Households

0

5

10

15

20

25

30

1951 1961 1971 1981 1991 2001

Canada Ontario

Source: FRPO based on Statistic Canada Census, various years.

Miron (1989) documents in some detail a rapid undoubling of both families and nonfamily households in Canada over the post-war period. He shows that the number of families not maintaining their own dwelling drops from 10 percent of the population in 1951 to 3 percent in 1986, led by a “rapid rise in the propensity of husband-wife families under 35 to maintain a dwelling”. He also documents the rapid expansion of non-family households, which include the single person households demonstrated above, and people sharing accommodation, led by young cohorts, particularly women. Miron points out that “it was among the poorer families that household formation increased most rapidly” and that “nonfamily persons also typically had quite modest incomes”. He shows that per capita income in Canada increased by 190 percent between 1951 and 1986, while household income increased by only 120%. Similar data is show for Ontario in the chart opposite for the 1981 to 2001 period. Here we see that this trend has continued, as real per capita income grew by 18 percent during period, compared to 14 percent for household income. Rising per capita income allows more people to form


11

independent households. Based on this analysis, Miron suggests government attempts to address housing affordability may be analogous to attempts to solving congestion by building roads. The “first law of traffic congestion” argues that congestion cannot be solved by building new roads, because this would simply lead to new traffic congestion. Altogether, the analysis of the previous two sections reveals a major flaw in traditional measures of housing affordability. Recall our first chart on page two of this paper which showed a traditional housing affordability indicator - the number of tenant households spending more than 50 percent of their income in rent. This chart showed a worsening of housing affordability conditions, giving a false sense of the trend in housing affordability. The problem stems from the use of household as opposed to per capita income data, and from the focus on tenants rather than the overall population. In fact, it appears that rising incomes have allowed more people at the margins to form their own household unit, and allowed higher income renters to become homeowners. Housing is a strongly desired commodity, and these changes undoubtedly represent a major improvement in the quality of life for these households. Rising living standards resulting from improving incomes shows up in our current housing affordability indicators as worsening conditions5. This is a very serious flaw with current affordability indicators.

Source: FRPO based on Census, various years.

Average Household Income vs. Per Capita Income, $2001, Ontario

39,000

49,000

59,000

69,000

1981 1986 1991 1996 2001

Aver

age

Hous

ehol

d In

16,000

18,000

20,000

22,000

Aver

age

Per C

apita

Inc79,000

89,000

com

e

24,000

26,000

ome

Average Household Income Per Capita Income

Given the above, the chart opposite updates our earlier indicator of average rents compared to lowest quintile family income to a per capita basis. Here we see that although housing affordability worsened in the 1986 to 1996 period, it has since improved dramatically for low income persons. Affordability is now better than it was in 1981. Another benefit of using per capita income is that it provides a better indication of a household’s “after-housing” discretionary income – the amount of money the have left after they have paid for their housing to pay for food, clothing and other necessities.

Average Rent Vs. Lowest Quintile Family Per Capita Income, Ontario

160

170

180

190

200

210

220

Per

cent


5 A numerical example may help. Suppose two people with low incomes share an apartment. If they both have an income of $20,000, the household income is $40,000. If their rent is $900, they do not have a housing affordability problem. Now suppose both have a large increase in income - $5,000 annually each (25%), and that, in response to their new income, they each decide get their own apartment. If they each get a new apartment with a lower rent, say $800, they are now each spending 38% of their income in rent, and are considered to be in Core Need.


12

Drop in Income of Young Workers Morisette (1995) found that real hourly wages of young workers dropped by more than 10% during the 1980s. Morisette and Bérubé (1996) find that spells of low income for workers under 35 lasted longer and resulted in lower real wages during the 1985-92 period than they did during the 1976-84 period. Beach and Finnie (2004) find a decline in the real earnings of entry level workers aged 20-24, both men and women. There was a steady upward shift of earnings for those entering the labour market in the 1960s and 1970s, following by a downward shift in the 1980s and 1990s. The authors find the changes to be highly cyclical and correlated with the recessionary years, and there is evidence of recovery since 1994 associated with the economic recovery in Canada.

Immigration The pattern of immigration to Canada has been changing, which appears to have had an impact on Canada’s and Ontario’s distribution of income. As the chart to the right demonstrates, Europe used to be the predominant source of immigration to Canada, but this has been on a downward trend since the mid 1960s. In contrast, immigration from Asia grew extraordinarily beginning in 1987.

Annual Immigration to Canada by Country of Origin

0

50000

100000

150000

200000

250000

300000

1955

1957

1959

1961

1963

1965

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

Europe Asia Other

Source: Statistics Canada.

This also corresponded with a much higher level of immigration to Canada beginning in this period. Average annual immigration to Canada was about 145,000 people in the 1970s, and 126,000 in the 1980s. Since then, immigration has averaged 224,000 people annually. At the same time, these new immigrants have not been faring as well in Canada’s labour market as their European predecessors. Picot and Hou (2003) find that the low income rate among recent immigrants doubled between 1980 and 1995. Picout and Hou find that the rise in low income rates in Ontario was particularly concentrated among the immigrant population, and that low-income rates have been falling over the past two decades among the Canadian born population. Low income rates rose primarily from the newer regions of origin: Asia (except Southeast Asia), Africa and Southern Europe.


13

Frenette and Morisette (2003) find that recent male immigrants experienced an average seven percent decline in real earnings compared to their counterparts in 1980. They also find widely different trends across sub-groups. Young men (25-29) with no university degree saw their incomes fall by 14 percent, while those with university degrees recorded a 3 percent increase in earnings. However, men aged 30 to 54 all experienced a large decline in income, whether they had a university degree (-15%) or not (-19%). Canadian born men in this category fared much better. Ayedimir and Skuterud (2004) find that one third of the decline can be attributed to language factors, and another third to a decline in the value of foreign labour market experience. This latter decline occurred almost exclusively among men from non-traditional source regions, which include Eastern Europe, Africa and Asia. Ferrer, Green and Riddel (2004) find that half of the earnings differential between immigrant and native born workers can be explained by lower levels of literacy amongst immigrants. All studies show that the immigrant-native born earnings gap declines as immigrants acquire earnings experience, and disappears after 17-21 years (e.g. Picot and Hou, 2003). This perhaps explains the optimism of recent immigrants, as survey data shows 58 percent have intentions to buy a home (Statstics Canada, 2003). As we would expect given the above, Engeland et al (2004) find that the percentage of recent immigrant households in core need in Canada’s CMAs in 2001 was 13.7 percent higher than non-immigrants. In the Toronto CMA, 43.5 percent of recent immigrant renters were in core need in 2001. Finally, the likelihood of being in core need declines the longer they have been in Canada. Appendix A of this paper demonstrates that immigration trends for Ontario mirror national trends, so that findings from the national studies are applicable to Ontario.

Ageing Population The number of seniors in Ontario is growing. Since household incomes typically fall once they stop working, this trend would tend to reduce average income statistics for the population. For many of these, high housing affordability costs likely reflect retirement, and not necessarily material poverty. Steele (2002) finds that seniors have a low participation rate in the Quebec housing allowance, and attributes this to relatively high wealth and higher level of permanent income of a significant portion of this population.

Ontario Renters by Age of Household Maintainer, 1981 and 2001

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Under25

25-34 35-44 45-54 55-64 65-74 75+

1981 2001

Source: Census, 1981 and 2001.

With respect to renters specifically, they are also aging generally. The movement of the baby boom generation through the


14

rental market is demonstrated in the chart opposite. There has been a significant reduction in the number of households with head under 25 years, and large increase in the number in those aged 35 to 54 years. One would expect this trend to reduce the number of households spending a large portion of their income in rent, as a household’s in these high age ranges typically earn significantly more. The fact that this has not happened suggests that the explanations for changing renter household income discussed earlier have been more than offset the impact of ageing. These are discussed further below. Firstly, immigrants make up a high portion of renters. A large portion of these immigrants are in the growing age categories shown above, and their incomes have been declining. Secondly, there is constant turnover in the rental market, with a large number of younger households who leave each year for home ownership, replaced by a new group of younger households. As we saw earlier, the incomes of the relatively new and younger renters have been declining, and lower incomes have persisted for longer periods. Since the younger age groups still dominate the age distribution in rental housing (the 25-44 age group is still the largest), this may also explain why the slower rate of growth in renters incomes. Finally, the previous section just demonstrated that household size has been shrinking, and that a growing portion of these renters are single person households who are forming their own household, and that this results in lower average household incomes. Finally, household formation and demographic changes to household types are clearly having a major impact on household income.

Immigrants by Age Group, Ontario, 2001

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

Under15 years

15-24years

25-44years

45-64years

65-74years

75 yearsand over

Source: Statistics Canada Census, 2001.


15

TRENDS IN HOUSING COSTS The other component of the traditional housing affordability ratio is the cost of housing. We examine trends in the cost of housing in this section.

Average Gross RentOntario, Constant $2001

0

100

200

300

400

500

600

700

800


When looking at real rents from Census data, we see that real rents rose significantly during the 1980s. Between 1981 and 1991, they rose from $646 to $778 in constant $2001, a 20 percent increase. Real rents then fell in the mid-1990s, and have since recovered somewhat. Nonetheless, real rents remained 18 percent above their 1981 levels. The increase is primarily due to changes that took place in the 1980s. This pattern of change in costs is not unique to renters. As the chart opposite shows, owners also experienced a large increase in the real cost of their housing between 1981 and 1991. Real housing costs rose by 22 percent between 1981 and 1991, and remained 22 percent higher thereafter. Ownership costs therefore have risen faster than rental housing costs over this period. The trend towards rising housing costs is not specific to rental housing.

Average Owners Major PaymentsOntario, Constant $2001

0100200300400500600700800900


Owners’ major payments from the census include payments for electricity, oil, gas, coal, wood or other fuels, water and other municipal services, monthly mortgage payments, property taxes, and condominium fees. A number of these variables would also influence rents, which in Ontario are commonly incorporated within the rent. Interest rates would influence both rents and mortgage payments.

Average MLS Sales PriceToronto CMA, Constant $2001

0

50,000

100,000

150,000

200,000

250,000

300,000

1981 1986 1991 1996 2001Source: FRPO based on TREB data.

As we see from the chart opposite, the purchase price of the housing appears to be a major factor in explaining changes in ownership costs. Average home prices in the Toronto CMA increased by 55 percent between 1981 and 1991 in real terms. They subsequently fell in 1996, before recovering to a level that remains 41 percent higher in real terms in 2001 compared to 1981.


16

Local Trends While we have been looking at province wide trends, there can be local differences in the real estate market. The charts below show historic CMHC rents by bedroom type for the London CMA and Toronto CMA. The universe of rental housing covered by CMHC rent survey data represents slightly less than half of Ontario’s rental stock. The type of housing included in the target universe in the sample survey remains fairly consistent throughout time. On the other hand, the type of housing excluded has been a growing component of the rental stock over time. This will be discussed in subsequent sections of this paper. Therefore, CMHC data is not as comprehensive an indicator of overall market rents as the census data cited earlier, suggesting caution in any use of CMHC data as general market price index.

London CMA Average RentsConstant $2003

$500

$550

$600

$650

$700

$750

$800

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

Source: FRPO based on CMHC rents and Statscan CPI.

As the charts show, not all marketplaces experience the same rental cost trends. London’s rents have cycled up and down, but have not changed significantly in real terms since 1985 (London data was only readily available back to 1985). Rents remain below their real peak reached in the mid 1990s. Toronto’s CMHC data shows a dramatic drop in real rents in the 1970s, and fairly steady increases in real rents during the 1980s and 1990s. Real rents have begun to moderate in Toronto, a trend which most analysts expect to continue for the next two or three years.

Toronto CMA Rents Constant $2003

$500

$600

$700

$800

$900

$1,000

$1,100

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Source: FRPO based on CMHC rents and Statscan CPI.

Comparing more recent trends in ownership and rental costs, data for the Toronto area since 1998 is shown in the chart opposite. Here we see that ownership prices have increased significantly more than rents in the past three years. There is continuing strength in the ownership market, but a clear softening in the rental market.

Toronto CMA Resale Prices vs. Rents, Percent Change, 98-04

-2

0

2

4

6

8

10

1998 1999 2000 2001 2002 2003 2004

CMHC Rents MLS Prices

Sources: CMHC and TREB.

Percent


17

EXPLAINING THE TRENDS IN HOUSING COSTS

Are Construction Costs Behind the Changes in Housing Costs? One obvious possible explanation for a rise in housing costs would be a rise in the cost of construction inputs (assuming demand remains constant). Since newly constructed homes represent a significant portion of the homes offered to the marketplace each year, these costs would have a strong influence on the cost of purchasing a home in Ontario. The chart below shows a long time series of the two major input costs for new housing construction: land and construction costs. The red line is an index of real (inflation adjusted) land costs in Ontario since 1961. It was compiled from the CMHC land cost index for newly financed homes from 1961 to 1978, and completed based on Statistics Canada New House Price Index, Land Only for the remaining years. It shows that land costs spiked dramatically in Canada in the 1970s. Land costs dropped significantly in the early 1980s, almost back to their level of the early 1970s. Then, in the real estate boom of the late 1980s, land costs spiked dramatically again. Since the early 1990s, land costs have been on a downward trend in Canada. The black line is a polynomial trend line for the land costs, to help even out the peaks and valleys of the economic cycle. What it effectively shows is land costs on an upward trend throughout the 60s, 70s, and 80s, and on a downward trend in the 1990s. Land costs are still 40 percent higher in real terms currently than they were in the early 1960s or early 1970s. Construction costs followed a similar pattern, but were not nearly as volatile as land costs. The blue line in the chart is an index of real construction costs since 1961. It has been compiled from CMHC’s Index of Construction costs (1961 to 1983) and Statistics Canada’s Index of Owned Accommodation Replacement Costs. Construction costs increased throughout most of the 1970s, but fell during the recession of the early 1980s. Construction costs again increased during the real estate boom of the late 1980s, and once again fell during the 1990s. In real terms, construction costs do not appear to be any higher than they were in the late 1960s and early 1970s.

Real Land Costs and Construction Costs, Canada, 1961-2002

100

120

140

160

180

200

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

Real Land Costs Real Construction CostsPoly. (Real Land Costs)

Source: FRPO, compiled from various Statistics Canada indices, and CMHC Land Cost Index for NHA financed dwellings.

1961 = 100


18

To see if this trend holds true in Ontario, readily available data was also compiled for the Toronto area from the Statistics Canada New Home Price Index, and adjusted for inflation. The results are shown in the chart below. This chart begins in 1976, close to the peak in land costs shown in the nation chart. The same post-1976 trend observed in the national data is seen in the Toronto area. Real costs fell dramatically in the early 1980s, and then rose again dramatically in the late 1980s. Since then, real costs have been on a downward trend. Certainly trends in the Toronto area mirror the national trend. Altogether, the data suggests that land costs are the dominant factor behind increasing housing costs.

Are Housing Quality Changes Behind the Changes in Housing Costs? To the extent that Canada’s and Ontario’s housing stock is improving in quality, we might expect this to explain some of the increases we found earlier in housing costs.

Real New House Price Index Toronto, 1976-2002

40

50

60

70

80

90

100

110

120

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

Land Only House Only Total Selling Price

Source: FRPO based on Statistics Canada data.

1976=100

S )

The trends we found in our data match those found in the United States. The chart to the right shows the rising real cost of both existing and new housing in the U.S. since 1968. However, when quality is held constant (this is sometimes referred to as hedonic pricing or a hedonic price index, a process of accounting for changes in quality to allow goods to be compared over time), we see that the real cost of housing is much flatter, and has not changed much.

CPI Data – Quality Adjusted In Canada, the Consumers Price Index (Census data and CMHC data shown earpurpose of tracking movements in price


ource: Quigley & Raphael (2004

CPI) is a quality-adjusted price index. Unlike the lier, CPI data is actually gathered for the express s over time. Attempts are made to adjust for

19

changes in quality in the CPI. This might include, for example, the addition of parking, cable, new or better appliances, changes in size, etc. The time series opposite shows the CPI rent index for Ontario adjusted for inflation. This data shows real rents have declined significantly, by almost 40 percent in real terms since 1971. The index shows a sharp drop in real rents throughout the 1970s, and finds that rents have been flat ever since.

Real Rents In OntarioReal CPI Rent Index, 1971=100

50

60

70

80

90

100

110

120

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

Source: FRPO based on Statistics Canada CPI All Items, and Ontario Rented Accommodation.

There has been some discussion in the academic literature that Canada’s CPI rent index tends to understate the level of inflation (e.g. Goy and Steele, 1994). The author is not aware of an empirical Canadian study which demonstrates this bias or its magnitude. The assumption of Canadian bias appears to have been based on U.S. studies. Randolph (1988) estimated the U.S. CPI rent index had a downward ageing bias (failure to account for depreciation) of 0.3 percent per annum. Crone et al (2001) report a downward bias due to nonresponse (surveyors lose track of tenants after they move, or cannot get rent information for vacated units), and suggests this bias was much larger in the 1940-77 period than after due to methodological changes, but still present. However, the Boskin Commission report (Boskin et al, 1996) reports a quality related upward bias: “for the period since 1970 we find it plausible that the CPI accurately measures rent per square foot of apartment space, but its measure of shelter rent is upward biased by neglecting the increase in the quality of apartments per square foot” (pp. 24). Discussions with Statistics Canada staff6 suggest that assumptions of Canadian rent index bias based on U.S. studies may not be relevant: quality adjustments are made in Canada, not in the U.S., and a different survey methodology, particularly regular sample turnover, makes the non-response problem less of an issue here.7

CMHC and Census – Not Quality Adjusted CMHC and Census data show real rents rising over the period 1971-2001 period, but are not quality adjusted. Fortin and Leclerc (2000) find that lack of quality adjustment in housing price data creates average upward bias of 1.65 percent per year. Hosios and Pesando (1991) also find that failing to adjust for quality changes added 2.03 percent to annual increases in MLS data. This is a significant upward bias.

Average Annual Private Rental Housing Supply by Type

Ontario, 1986-1996

02,0004,0006,0008,000

10,00012,00014,00016,00018,00020,000

NonConventional

Traditional

Source: Clayton Research Associates based on CMHC and Census data.

6 January 7 phone conversation with Charles Berube of the Prices Division of Statistics Canada. 7 CPI rent data is collected through the Labour Force Survey, which is a rotating multi-stage stratified sample. Households in the sample are surveyed for a period of 6 months, and one sixth of the sample is replaced every six months.


20

We do know that the sources of rental supply have been changing in Ontario. As the chart above shows, non-conventional supply dominated new additions to Ontario’s rental stock between 1986 and 1996. Data for the city of Toronto corroborate this trend. Steele (1993) provides data on display ads by type of rental housing stock which shows that ads for condominiums and houses have made up an increasing portion of total ads in the Toronto Area since 1971. As the chart opposite shows, non-conventional rental supply has been growing much faster than traditional rental supply in the City of Toronto. Altogether, single-detached, semi and condo rentals increased by 27 percent between 1986 and 1996, versus 16 percent for the remainder (mostly made up of traditional rental housing) of the rental stock. All this suggests data that is not quality adjusted will have an upward bias.

Rental Housing Growth Rates By Type, City of Toronto, 1986-96

0

5

10

15

20

Detached Semi/Row Rental Condo Traditional

Source: FRPO based on Metro Planning (1996) and The Starr Group (2000).

25

30

35

40

Trends in other indicators of housing quality lend support to the need to quality adjust pricing data. Below are some charts which demonstrate substantial improvements in the quality of Canada’s housing stock between 1951 and 1977.

Percent of Housing Stock With Bath or Shower Facilities, Canada

0102030405060708090

100

1951 1961 1966 1971 1976 1977

Source: CMHC, Canadian Housing Statistics, 1977

Percent of Housing Stock With Flush Toilets, Canada

0102030405060708090

100

1951 1961 1966 1971 1976 1977


Percent of Housing Stock With Hot and Cold Water, Canada

0102030405060708090

100

1951 1961 1966 1971 1976 1977


To quote CMHC on this trend nationally: “Housing quality has improved steadily over the post war period. For example, in 1951, 9.4 percent of the stock lacked basic plumbing facilities, a fraction that dropped to 1.6 percent in 1982. The absence of such facilities is now so rare that data on the presence of basic services are no longer collected by the Census. Over the last number of years, the general trend has been toward the production of larger, more durable and more energy efficient homes that have more amenities. They frequently contain special features such as family rooms, double-attached garages, and two or more bathrooms (CMHC, 2003).” As discussed by CMHC, plumbing improvements are not the only indicators one would look to for housing quality improvements. There have undoubtedly been a number of other improvements over the last 30 years, which may have included electrical services,


21

heating and insulation properties, and so on. However, the plumbing indicators certainly illustrate the point that the quality of our housing stock has been improving over time. Housing quality has historically been an important element of Canadian housing policy. There was a time in Canada when improving physical housing conditions dominated public policy discussion. It is not uncommon for housing programs to have minimum standards, a clear expression of a public desire to raise the level of housing consumption (i.e. level of expenditure) of low income households. Quality improvements are the “good news” about rising housing costs..

Conclusion: Housing Prices Have Been Flat Taken altogether, it seems likely that the quality-adjusted real rate of rent increases in Ontario have been somewhere between the decline shown through the CPI data and the real rate of increase shown in the CMHC and Census data. The CMHC and Census data have a demonstrated upward bias, and the CPI may have some downward bias (although this is disputed). The fact that the CPI rent index is specifically designed to account for price changes, and is quality adjusted, may lead one to favour this price indicator. Therefore, it seems reasonable to assume that housing costs have been relatively flat over the past 25 years, as they have been in the U.S., or may even have fallen. This means that traditional shelter cost to income ratios using Census data do not reflect changes to the quality of the housing, which some may consider important and a significant shortcoming. An affordability indicator which accounted for such changes would show even greater improvements in housing affordability over the past 25 years.

Are Housing Size Changes Behind the Change in Housing Costs? One quality characteristic deserves special attention - size. The size of dwellings in Canada has been increasing. The chart opposite shows the number of rooms per dwelling in Ontario from the Census. It has increased from 5.5 rooms per home in 1961 to 6.4 rooms per home in 2001. It clearly indicates an upward trend in size. While not adjusted for the size of the rooms, this would indicate an increase in housing size of about 16% from 1961 to 2001.

Average Number of Rooms Per Dwelling, Ontario

5

5.2

5.4

5.6

5.8

6

6.2

6.4

1961 1981 2001Source: Census, various years.


22

Another measure of size is CMHC data on the size of new single detached dwellings financed under the national housing Act. While not for the whole stock of housing, this data generally shows an upward trend in the size of the housing stock. Combining both sets of data, it would appear that the average size of new homes being built in Canada is larger in size than the average size of homes in the existing stock. This would tend to increase average housing costs, other things being equal.

Average Size of NHA Financed Single Detached Homes, Canada

85

90

95

100

105

110

115

120

Squa

re M

etre

s

1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991Source: Canadian Housing Statistics, CMHC.

Is The Tenant Protection Act (1998) Responsible for Increasing Rents? In an October 7, 2004 open letter to Ministry of Municipal Affairs and Housing (MMAH) stakeholders, the Honourable John Gerretsen suggested that the Tenant Protection Act (1998) allows “unlimited” rent increases that can “hardly be considered fair to tenants”. The letter says that “between 1997 and 2003, average rents across the province soared by 23 percent” and that rents have only dropped slightly after years of “double digit increases”. The government is clearly indicating its view that the Tenant Protection Act is the primary cause of housing affordability problems in Ontario. Therefore, we examine this particular issue more closely. A 23 percent rent increase over the period 1997-2003 constitutes an annual rate of increase of 3 percent. The chart opposite compares these “soaring double digit rent increases” with the cost of purchasing a home in Ontario over that same period. The cost of purchasing the average resale home in Ontario increased from $164,000 in 1997 to $227,000 in 2003, an increase of 38 percent. This represents an annual rate of increase of 5.5 percent, significantly more than the rate of inflation. Thus, it appears home resale prices are continuing to rise in real terms and may reach their 1991 peak fairly soon. To determine whether the introduction of the Tenant Protection Act has been the primary cause of increases in rents in this period, as asserted my Minister Gerretsen, we look at its impact on rents more closely.

Percent Increase in Resale Prices vs. Rents, Ontario, 1997-2003

2338

0

5

10

15

20

25

30

35

40

Rents Resale PricesSources: Ontario Ministry of Municipal Affairs and Housing, and CREA.


23

In the chart opposite, CMHC’s average rents for Toronto from 1990 to the 2003 have been plotted. Average rents started at $627 in 1990. This is then compared to a plot of the same starting rent, but it is increased by the annual rent control guideline. This way we can compare the rents actually being charged in the marketplace, with the “maximum rent” 8 the average landlord would have legally been entitled to charge if the Tenant Protection Act had never been introduced, and its predecessor, the Rent Control Act, had been left in place. As the chart shows, the soft rental market of the early 1990s meant that landlords were not able to achieve the level of rent increase they were entitled under the Rent Control Act. By 1998, many landlords would have had rents well below the legal maximum. Therefore, even if the legislation had not changed, most landlords would have been entitled to increase rent more than the annual guideline between 1998 and 2000 under the old rules. Landlords would also have been entitled to pass through above-guideline rent increases for any capital work done or for extraordinary utility costs, over and above guideline increases, even if the legislation had not changed in 1998.

Toronto Average Rents Since 1990 and Rents if Guideline Taken

$600

$700

$800

$900

$1,000

$1,100

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

CMHC Av. Rent Rent If Guideline Taken

Source: FRPO based on CMHC data.

Due to recent soft market conditions in recent years, rents have now fallen below what an average landlord would legally have been entitled to charge under the previous Rent Control Act, had there been no legislative change in 1998. This analysis suggests that the changes to the Tenant Protection Act have had a minimal long-term impact on rent levels in Ontario. Finally, recall our earlier findings that housing affordability conditions deteriorated between 1981 and 1996, under strict rent controls, and that housing affordability conditions improved dramatically between 1996 and 2001, after the Tenant Protection Act was introduced and had been in place for three years. This clearly defeats the hypothesis that the rent controls help housing affordability, or that the Tenant Protection Act has been responsible for deteriorating affordability. Rather, tracking housing affordability changes through time in Ontario shows that housing affordability conditions got worse as rent controls were tightened in the province, and improved once they were loosened. In subsequent sections, we will explore why it is that rent controls actually make housing affordability conditions worse.

8 'Maximum rent' was a legal concept: it was the rent charged at a date of record plus all increases that were allowable after that date, such as annual guideline increases and ordered above-guideline increases. For example, suppose the rent a landlord charged on a particular unit in 1990 was $1000, but that the landlord chose not to increase this rent for 8 years. By 1998, the landlord would have been entitled to charge $1,355 (calculated by applying the annual guideline to $1000), even though she may be charging the tenant significantly less. This concept was introduced so that landlords would not be penalized for offering tenants lower rents in a strict rent control system. Once the province moved to a less strict rent control system in 1998, maximum rents were no longer increased by the guideline, and the disappeared when a unit turned over.


24

FILTERING AND AFFORDABLE HOUSING Filtering is almost always ignored in affordable housing discussions, but there is growing evidence that a primary cause of affordable housing problems is a breakdown of the filtering process. Therefore, it is becoming increasingly important that we understand this concept in developing good public policy. The term filtering was first used by Hoyt (1939) to describe the process whereby households “move up a step, leaving the oldest and cheapest houses to be occupied by the poorest families or to be vacated”. Hoyt mapped out the distribution and growth patterns in 142 U.S. cities using average market rents. He found that those in high rent areas typically moved to the new homes far from the core (the suburbs) of the city. He also found that people with lower incomes moved into the homes being vacated by those moving to the suburbs. Ratcliffe (1949) is widely credited with first formalizing the theory. He describes the filtering process as follows:

• housing tends to move downward in value and quality as it ages • the housing that is introduced at the top descends gradually through successively

lower value strata • new housing introduced at upper-income ranges releases used homes, which are

passed down to successively lower levels until the effect reaches the bottom of the market

Since then, filtering has been extensively discussed in the academic literature. The proper definition has been debated and refined. Elaborate theoretical models of the process have been developed, and a numerous empirical studies have been undertaken.

Empirical Studies of Filtering The empirical studies examining this process have used a variety of approaches to examine the impact of filtering on housing markets generally, and to evaluate the extent to which the filtering process provides benefits for low income households. What follows is a summary of the findings of only some of these studies (there are too many to list them all) . Fisher and Winnick (1951) analyzed data on the housing stock in New York’s Lower East Side from 1900 to 1940 and found there was downward filtering of housing. The authors summarized the filtering process follows:

“As newer units are added (generally at higher than average rents), the community standard is raised; and statistically the mean or median of the distribution is shifted to the right; most existing units are further to the left. Demolition of the lowest-priced (and presumably the poorest)


25

housing will have a similar effect by raising the average quality of the housing inventory.”

Smith (1964) used data from Oakland neighbourhoods from 1936 to 1960 and found that the strongest filtering tendency was for transfers from middle-income households to low-income households. Weicher and Thibodeau (1988) undertake a rigorous empirical test for filtering. In particular, the authors look for positive benefits for low-income households from filtering, a matter which remained in debate from the theoretical models. They find strong empirical evidence that filtering from private production does provide positive benefits for low-income households. Malpezzi and Green (1996) demonstrate that the supply of lower-quality, lower cost housing is primarily dependent upon the quantity of new, higher-cost and higher-quality housing supplied in any given market.

Vacancy Chain Studies A branch of research which has become know as vacancy chain analysis began with the work of Kristof (1965). He looked at the “chain of housing turnover generated by people moving into new constructed units”. Kristof found that, on average, families with lower incomes moved into the housing vacated by their predecessors Lansing, Clifton and Morgan (LCM) (1969) undertook the largest and most comprehensive vacancy chain survey that has ever been attempted. They interviewed the occupants of 1,133 newly occupied homes and subsequently followed the chain of vacancies created behind them. Following each vacancy chain to its conclusion, the authors completed 3,039 interviews in total in 1966. The authors found that, on average, each new home constructed creates 3.5 moves. They found that, as you move down successive steps in the vacancy chain, the homes get lower in value, and the income of the households gets lower. They also find that the higher value of the new homes, the longer the length of vacancy chain sequences created. Finally, for every 1000 new homes built “about 333 poor families will be included in the sequences begun by the 1000 new homes.” Interestingly, they find that poor families benefited most from moderate cost ownership housing, rather than low cost rental housing, because of the longer vacancy chains created by this housing. The authors conclude that “the poor are indirectly affected by the construction of new housing even if they do not occupy the new housing” and that “the poor will benefit from any policy which increases the supply in the total market.” Brueggeman (1970), Sands (1971) and Sands and Bower (1976) and also conduct vacancy chain studies, and compare the vacancy chain effects of different kinds of housing. All confirm a filtering effect from new construction. Sands (1977) finds that


26

all types of housing, even the most expensive, have a substantial impact on the supply of low-cost housing opportunities. Marullo (1985) uses 1977 data from the U.S. Annual Housing Survey (AHS) of 70,000 households by the U.S. Department of Housing and Urban Development on those who had moved within the past 12 months, but does not look at newly constructed homes. He finds vacancy chain lengths similar to that of LCM (1969). Brescia (2003) uses 1983 AHS data, but isolates the impact of newly constructed homes on vacancy chains. He finds that every high cost newly constructed home creates 0.48 vacancies for a low-income household.

FRPO Filtering Study The author is not aware of a comprehensive vacancy chain study of the Ontario housing market. However, the Federation of Rental-housing Providers (FRPO) conducted a survey of tenant households who moved into newly constructed rental housing units in Toronto and Ottawa in 2003. Information the rent being paid in the new rental, and the rent (if any) of their previous home was gathered for 168 tenants. The results (previously unpublished) are shown in the chart below. The average rent being charged in the newly constructed units in the survey was $1,362, and the range of new rents was $1075 to $1780. Forty-five of the 168 households surveyed were new households, and so had no previous rent. It may be fair to assume that the new construction diverted many of these households from the existing rental stock: had the new rental buildings not been built, many of these households would have moved into the existing stock. The remaining 123 households moved from the existing rental stock. The distribution of the rents for the units they vacated is shown in the chart opposite. As you can see, even though new rental construction comes in at the high end of the rental market, it attracts people from the existing stock. The distribution of previous rents is very similar to the distribution of overall rents in Toronto and Ottawa. The average rent of the units vacated was $989, $373 less than the average rent for new construction. Furthermore, not even counting for the diversion of new households from the existing rental stock, the first series of vacancies created by the new construction created 39 vacancies in rental units renting below $800.

Previous Rent, 123 Recent Movers to Newly Constructed Rental Housing

Toronto & Ottawa, 2003

02468

1012141618

Num

ber

of M

ove

$ 0-399

$ 400-499

$ 500-599

$ 600-699

$700-799

$800-899

$ 900-999

$ 1000 ...

$1100 .. .

$1200 ...

$1300 ...

$1400 ...$1500 +

Source: Federation of Rental-housing Providers of Ontario.

New Construction Average Rent $1,362


27

Information on the location of the previous residence was not available for all households. However, where it was available it was found that the vast majority of new tenants moved from within the same Census Metropolitan Area (CMA). Approximately 11 percent moved from outside the CMA of the new rental building. Most of those (7%) came from elsewhere in Ontario. There are two limitations to this survey. Firstly, it is only a first stage vacancy chain analysis. A full vacancy chain analysis would result in a longer vacancy chain, and very likely point to an even larger number of vacancies being created in the existing housing stock. The second limitation is that it is that only rental housing is surveyed. Rental housing has a much shorter average vacancy chain than new ownership construction, because a high proportion of renters are newly formed households. Both of these shortcomings tend to considerably understate the filtering benefits of new construction in Ontario, so reinforce that filtering is an important element of housing allocation in Ontario.

Why Filtering Is Important? Filtering is important, because it is our primary source of affordable housing. It is the means by which the typical North American household has seen improvements in the quality and affordability of their housing over the past century. As we will see in the next section of this paper, the evidence is growing that what is most important in ensuring an adequate supply of low cost housing is ensuring that there is an abundant supply of housing, regardless of its price. Most new supply is higher in cost than the existing stock. Problems with housing affordability are greatest in those areas where there are barriers to new supply generally. This happens because the tap at the top of the filtering process gets shut off. Once new supply is restricted, fewer housing opportunities are created at the low end of the housing market for low income households. The beauty of the filtering process is that it happens without requiring any government funding. Households with higher incomes pay for the higher cost of new construction, and leave behind housing that may be less desirable than the new stock, but is most often good quality housing desired by low income households. Since the barriers to new supply are most often regulatory, it also means that there is little or no cost to the government in implementing policies which eliminate or reduce those barriers. Given government’s limited resources, pursuing such policies should be seen as very advantageous.


28

GOVERNMENT REGULATORY BARRIERS AND AFFORDABLE HOUSING Our investigation thus far has found distinct trends in both housing costs and housing consumption patterns. We have also found evidence that an adequate supply of housing generally is one of the most important determinant of housing affordability conditions in a region. These are all areas where government rules and regulations can have a significant impact. The trends we have uncovered in Canada and Ontario have mirrored those in the United States. This is not surprising, given the similar histories of population growth and settlement patterns in both countries. These similarities allow us to take advantage of detailed housing policy research in the U.S., in addition to research in Canada. We now look at several distinct areas where there is concrete evidence that government regulations have a major impact on housing affordability conditions.

Land Regulation and Zoning Our research has shown that there have been increases in the real cost of housing over the past 30 years. In particular, land costs have increased significantly. Our findings also show that Ontario is experiencing many of the same housing structural and affordability problems being experienced in the U.S. Mayer and Somerville (2000) show that land use controls have a significant impact on new supply. Using quarterly data from a panel of 44 U.S. metropolitan areas between 1985 and 1996, the authors find that land use regulation lowers the level of the steady-state of new construction, and lowers the elasticity of supply. The estimates suggest that metropolitan areas with more extensive regulation can have up to 45 percent fewer housing starts. Similar findings were reached in studies by Green, Malpezzi and Mayo (1999), Mayo and Sheppard (1996), Green (1999), Malpezzi (1996), and Pollakowski and Wachter (1990). Malpezzi and Green (1996) demonstrate that through the process of filtering, the supply of housing for low income households is highly sensitive to the production of new, higher quality and higher cost housing. If governments regulation restrict supply, they turn off the tap at the top of the filtering process. The authors examine detailed data sets from the 1970s, 1980s and 1990s. In the author’s words, “to the extent that a city makes it easy for any type of housing to be built, it will also enhance the available stock of low-cost housing”. They find that restrictive regulations (including rent controls) are a common thread across those markets that have difficulty producing low cost housing. They find that moving from a relatively unregulated market to a highly regulated market results in


29

an increase in lowest quartile house values by 60 percent, and lowest quartile rents of 21 percent. The largest price effects for these regulations occur at the low end of the market. Fishchel (1990) finds that municipalities that have growth controls have higher housing prices. These growth controls can include moratoria on new developments, urban growth boundaries, or open space requirements. Similar results were found by Levine (1999) for areas of California. Not surprisingly, empirical research also finds that zoning restrictions (restrictions on use, density restrictions, and so on) lead to higher housing prices and reduced construction. See for example Thorson (1996). Glaeser and Gyourko (2002) find evidence that suggests that zoning and other land use controls play the dominant role in making housing expensive in those areas where housing costs are above the marginal cost of construction.

Rent Controls as a Supply Barrier As we have seen above, regulatory barriers to housing supply are a major cause of housing affordability problems. Therefore, to the extent that rent controls reduce housing supply, they are a cause of housing affordability problems. Overall, Ontario’s housing market appears to be working relatively well at providing new housing for its population. The chart opposite shows the total housing supply in Ontario broken down by those starts intended for the rental market, and those intended for the ownership market. Over the 1970 to 2003 period, an average of 69,000 new homes were built in the province each year. The strong real estate cycle is evident in the starts data.

Housing Starts by Intended Market Ontario, 1970 to 2003

0

20,000

40,000

60,000

80,000

100,000

120,000

70 72 74 76 78 80 82 84 86 88 90 92 94 96 98 00 02

Private Rental Ownership

Source: FRPO based on CMHC and Ontario Ministry of Municipal Affairs and housing start data.

The chart shows that traditional rental starts used to make up a significant portion of Ontario’s housing starts. In the early 1970s, purpose built rental housing made up about one third of Ontario’s housing starts. By the mid 1990s, purpose built rental housing starts made up less than two percent. By comparison, in the US, rental housing starts


30

have still made up 11 to 17 percent of new housing start over the past 10 years. Rent controls still impact large parts of New York, New Jersey and parts of California, depressing construction in these areas, but the majority of the country is free from rent controls, so the dampening impact of this regulation is less prominent. Altogether, rental starts declined by 96 percent from their pre-rent control levels of 27,195 annually to an average of 1,170 under the strictest rent control regime in Ontario’s history, the Rent Control Act, which operated between 1993 and 1997.

Average Annual Private Rental Housing Starts, Ontario

0

5,000

Pre Rent Control(1970-1974)

Rent Control Act(1993-1997)

Source: Canada Mortgage and Housing Corporation.

10,000

15,000

20,000

25,000

30,000

The chart opposite isolates some key watershed moments in the history of rent controls in Ontario. When rent controls were first introduced, they had a devastating impact on supply. Some federal programs and tax incentives were then introduced in an attempt to bolster supply in the 1970s and early 1980s. Other factors such as federal lifetime capital gains exemptions, the up front deductibility of soft costs, and a real estate boom in the late 1980s, combined to lead to an increase in rental starts in the late 1980s. However, there was a major rent control tightening in the early 1990s9, and starts spiralled downwards once again. Finally, rent controls were softened modestly in 1998, and there was a subsequent modest recovery in rental starts. However, given the volatile history of rent regulation in Ontario, investors remain naturally wary of future legislative changes, which likely had a significant dampening effect on rental starts.

Ontario Private Rental Starts1970 to 2003

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

70 72 74 76 78 80 82 84 86 88 90 92 94 96 98 00 02Source: Ontario Ministry of Municipal Affairs and Housing and CMHC.

Rent controls introduced

Major rent control tightening

Rent Controls Softened

Purpose built rental housing is vulnerable to political attack in Ontario, which has driven investors out of the market. The constant nature of the political attacks on the industry over time has meant that investors are also very reluctant to enter the market again. There are other factors which influence supply. Certainly rents have lost ground relative

9 Bill 4, An Act to amend the Residential Rent Regulation Act, was introduced in November of 1990. It retroactively took away the right of landlords to recoup the cost of capital projects already completed and approved under existing legislation.


31

to new ownership housing prices (but rent controls may also be a factor here), making rental development less attractive. Federal taxes and municipal fees and charges have also had an impact. However these taxes (e.g. the GST) and municipal fees have also impacted the ownership market, and the commercial real estate market, yet these markets have not been nearly as damaged as the rental market. The primary cause of decimation in traditional rental starts has been rent controls.

Rent Controls and the Unregulated Market It is a common mistake to assume that “traditional” rental housing starts (those starts where CMHC identifies the target market as rental) are the only source of rental housing supply. As we saw earlier, rental supply in Ontario now comes primarily from non-traditional sources. The primary impact of rent regulation has been to drive rental supply into areas which are less affected by the rent regulation. Just because a housing start is “categorized” as intended for the ownership market does not mean that either the “intention” was properly identified, or that the housing remains in the ownership market. As we saw earlier, the majority of new rental supply in Ontario now comes from non-purpose built rental housing. The chart to the right demonstrates this for one submarket alone. It shows that the Toronto rental market was supplied by approximately 8,000 new condominium rental units in 2002-03, versus 1,300 traditional rental units. Although these rental units were intended for the rental market (they are being bought by investors), they are not categorized as rental starts. This type of rental housing is more difficult to regulate. It is harder to monitor and apply strict rent controls on a unit by unit basis in the province, so many of these units fly below the rent control radar. In addition, they can always be pulled from the rental market should any future government attempt a political attack. This escape hatch is generally not available to the owners of purpose built rental housing. Research has shown that rent controls drive up rental housing costs in the uncontrolled sector, and sometimes in the controlled sector as well. Early and Phelps (1999) examine data from 49 U.S. municipalities from 1984 to 1996 and find rent controls increased rents in the uncontrolled sector. Fallis and Smith (1984 and 1985), also found that rents in the


32

uncontrolled sector in Los Angeles and Toronto were higher than they would have been in the absence of rent control. Caudill (1993) examined the role of controls on New York City housing prices in 1968. His estimates suggest that if controls were removed, rents in the uncontrolled sector of New York City would fall by 22 to 25 percent. Malpezzi (1996), using data across 54 large metropolitan areas, finds a positive and statistically significant relationship between the existence of rent control and median contract rent. In other words, cities that have rent control have higher average rents than cities that do not. This is likely true in Ontario, where the shortages caused by rent controls actually increase the rents that can be achieved in those sectors of the market where rent controls are less binding. Condominiums would be a classic example of this. As noted by Metro Planning (1996): “Throughout the 1980s, rent in the conventional sector (privately-owned apartment buildings) rose at about the same rate as tenant incomes. But with rising rents in other sectors (rented condos, basement apartments, etc.) and with slight income polarization, the share of tenants who paid too much in rent grew gradually over the decade.” Therefore, by driving up rents in the uncontrolled sector, the primary source of new rental supply once rent controls drive down starts in the controlled sector, rent controls actually worsen housing affordability.

Rent Controls and Filtering While rent controls clearly impact the supply of rental housing, probably their most significant impact on low income households happens on their impact on the allocation process for housing. Rent controls result in a number of behavioural changes in the marketplace that ultimately impact on the availability of low cost rental housing generally. The controls have an impact on household formation decisions, the rate of turnover of housing, and its distribution. By forcing rents below their market clearing price, rent controls mute or eliminate the price mechanism and cause the following: • Increased demand: household formation is greater than it would otherwise be.

Demand increases at the same time that supply is shrinking. • Hoarding: existing renters hold on to their bargain housing much longer than they

would otherwise. • Elimination of price-allocation: given that the owner’s revenues are being

constrained, while her costs are not constrained, the owner acts by allocating the housing in a way that is perceived to reduce costs associated with the tenancy.

The impacts above, combined with reduced supply, result in shortages. These were obviously manifested in Ontario’s largest rental market, Toronto, as low vacancy rates. Shortages do not happen when there is a price clearing mechanism. This is the hallmark of price controls everywhere they have been applied in the world. The Soviet Union pricing system is a classic example of this: prices were held very low, but there was


33

nothing on the shelves. Elimination of price allocation ultimately results in misallocation. Tucker (1991) demonstrates that the distribution of rents offered to the marketplace in rent controlled cities becomes skewed toward high rents as a result of the shortage. Rents at the low end of the market are no longer offered for rent through local newspapers. Toronto is one of the markets where he identifies this problem. However, since rent controls were modestly softened in 1998, there has been a dramatic shift up in the vacancy rate at the low end of Toronto’s market. In fact, the vacancy rate is now highest in Toronto at the low end of the market, further illustrating Tucker’s point.

Toronto CMA Vacancy RateUnits Renting Under $800

0

1

2

3

4

5

6

1998 1999 2000 2001 2002 2003 2004

Source: CMHC.

Harvard economists Glaeser and Luttmer (2003) examined the misallocation of housing under rent control in detail for the New York rental market. They find that there is significant misallocation of housing under rent controls, leading to a large welfare loss for society. Salins (1991) reaches the same conclusion through a detailed neighbourhood examination of rental housing in New York, as does Pollakowski (2003). Nobel laureates Friedman, Stigler and Becker identify this as a major problem with rent controls. Goetze (1994) examined the impact of rent controls on the allocation of rental housing in Boston: “This study, based on extensive empirical data, makes clear that the special protection promised by rent control – for families, for less affluent households, and for the elderly – has failed. Instead, rent control has caused the gradual displacement of a large disadvantaged renter population by a younger, higher income, better educated, singles population. Rent control is paradoxical in that it produces the opposite of the promised results; it is an initially well-intentioned but ultimately destructive housing policy that actually reduces supply, hurts the poor and displaces the needy.” St. John (1993) uses a similar methodology for Berkely and Santa Monica and finds the exact same impact of rent controls. Lindbeck (1971) documented this very same problem in Sweden: “After seeing how low-income families in the rent-controlled city of Stockholm have waited in the official queue for apartments for five to eight years, while high-income families always can get apartments through good “contacts” or the black market, it is difficult to see the virtues of rent control as a tool of social policy.” Socialist economist Rydenfelt (1975) reached the same conclusion: “Large purses, of course, always meant advantages on the Swedish housing market, but never such enormous advantages as during the shortage years – the era of rent control. The rich man could solve his housing problem practically instantaneously [by buying, renting an expensive flat, or through the black market]. Not so the man with the low income.”


34

Stanbury and Vertinsky (1986), Steele and Miron (1984), the Region of Peel (1985), Marks (1984) and Thom (1987) reach similar conclusions in examining the distributional impact of rent controls on the Ontario market for the Commission of Inquiry into Residential Tenancies. This is just a very small sampling of the numerous independent studies which have reached the same conclusion. FRPO has summarized the findings of many of these and other studies in its series Existing Rent Controls are Working (www.frpo.org).

Property Tax Policies Another area of provincial and municipal jurisdiction which impacts on the cost of housing is the property tax. The property tax in Ontario is probably the most regressive tax in Canada. In Toronto currently, the a multi-residential renter is paying on average about $106 more per month than they would pay if they were taxed at the same rate as home owners. Much like cigarette taxes, this is a direct cost pass through to the tenant. In fact, provincial legislation requires that the full amount of property tax reductions be passed on to tenants. Many municipalities in Ontario charge over double the rate of property tax to tenants when compared to homeowners, although some have moved recently to correct this unfairness. However, in the major centres of Ontario, where the vast majority of renters live, the problem persists.

Monthly Property Taxes for Tenants vs. Taxes if Taxed Same as Owners

Toronto

$0$20$40$60$80

$100$120$140$160$180

Current If Taxed Same Rate AsHomeownersSource: FRPO.

In contrast to the higher taxes paid by tenants, the chart opposite compares the average income of homeowners in Ontario to renters. The average homeowner has double the income of the average renter. As a result, this unfair tax treatment of renters is highly regressive. Given the average rent in Toronto currently of $976, a $100 tax reduction would translate into an 11 percent rent reduction. If the province wishes to address the cost side of the housing affordability equation, this is probably the first place it should start.

Average Income, Homeowners vs. Renters, Ontario, 2001

$0$10,000$20,000$30,000$40,000$50,000$60,000$70,000$80,000$90,000

Renter OwnerSource: Statistics Canada, 2001 Census


35

http://www.frpo.org/

APPROPRIATE GOVERNMENT RESPONSES Now that we have reviewed the trends and root causes of housing affordability problems in Ontario, it is worth discussing some of the potential actions governments can take to best address these problems. We have found that housing affordability problems are primarily an income problem, so we will look at potential government responses to address this causal factor. We also found that land and housing supply can have a significant impact on housing affordability problems, so we look at possible actions in this area. Finally, we will suggest some changes to housing affordability indicators based on the shortcomings we found with current indicators. In particular, we will review the following potential strategies: • A government sponsored new “affordable housing” construction program; • Shelter allowances and Rent Supplements; • Special needs housing; • Eliminating unfair property taxation of renters; • Removing barriers to housing supply; and • Fixing affordability indicators and thresholds.

Government Sponsored New “Affordable Housing” Construction Program It has long been an intuitive response of public policy makers in Canada to attempt to address concerns about affordable housing by building new affordable housing. This has included public housing construction programs in the 1960s and 1970s, non-profit and cooperative housing construction programs in the 1980s and 1990s, the most recent federal “Affordable Housing Program”, and a variety of others. Given the preceding findings regarding the contributing factors to housing affordability problems, and the experience we have had with these programs, it is worth reviewing this common strategy.

Background: Costs of Government Sponsored New Construction We begin by reviewing Ontario’s most recent experience with a large scale new “affordable housing” construction program. Between 1985 and 1995, the province allocated funding for the building of well over 50,000 non-profit housing units under unilateral provincial housing programs. The chart to the right summarizes the average per unit costs and revenues for housing completed under this program as of 1996.


36

Average Monthly Costs and Revenues Per UnitOntario Non-Profit Housing Portfolio, 1996-97

RGI Rent $296

$800

$1,000

$1,200

Market Rent

Total Cost $1,127

RGI Subsidy

$380

$0

$200

$400

$600

Source: Ontario Ministry of Municipal Affairs & Housing.

$676

Supply Subsidy

$451

There were two categories of tenants under the program: those who received rent geared-to-income (RGI) subsidies, and those who were charged a market rent. This reflected a desire of the government to have income mixing in these projects, to avoid the creation of low-income “ghettos”, a perceived problem with the public housing programs of the 1960s and 1970s. The ghetto perception problem had made it difficult to get public housing projects built as they faced growing neighbourhood opposition. The average RGI tenant paid a monthly rent of $296, reflecting an average income of about $12,000. Market rent tenants were charged $676 on average. The difference between the market rent and the RGI rent was considered an RGI subsidy, which was then funded by the province. The total monthly cost of operating the average unit in the program was $1,127. The shortfall between this cost and the average market rent was also funded by the government. It was considered in effect to be a supply subsidy. Therefore, under the program, the non-profit corporation charged a total monthly rent of $1,127. For market rent tenants, they collected $676 directly from the tenant, and collected a $451 subsidy from the province. For RGI tenants they collected $296 directly from the tenant and received a subsidy of $831 from the province.

Comparing the Program’s Cost to the Cost of Other Housing The monthly rents charged by non-profit housing corporations are compared below to various types of market housing in 1996.

Average Monthly Housing Costs by Type of Housing, Ontario, 1996

$0

$200

$400

$600

$800

$1,000

$1,200

Core NeedAverage

Rent

CensusAverage

Rent

OwnersAverage

Shelter Cost

MonthlyCarryingCost Av.

MLS Home *

Non-ProfitHousingAverage

Rent

Sources: Census, Ontario Ministry of Municipal Affairs and Housing, CREA, Bank of Canada.

* Includes principal, interest, tax and utility payments

First, there are the rents being paid in private rental housing by those in core need. These are the target households for the affordable housing program. On average, the typical core need household was paying $613 per month in rent. This is almost half the rent of $1127 charged by the average non-profit housing provider under the new construction program. Since we found earlier that most households in core


37

need had suitable and adequate housing, or could get it if they had an income supplement, this difference of $514 can be considered to be the “new construction premium”: the added per household cost of trying to help these households by building new housing. The average tenant in Ontario paid $679 per month in 1996. The average cost of ownership for owners from the Census (Owners Major Payments) was $809. Finally, the ownership carrying cost of the average MLS home sold in Ontario in 1996 (at an average sale price of $156,662), including principal, interest and taxes, was approximately $1,122, slightly less than the monthly non-profit rent. This would have been made up of mostly single family homes. Therefore, on average, the size of these homes and the number of amenities (e.g. garages, number of bathrooms, etc.) would have been significantly greater than the homes in the government program.

Distribution of Gross RentsOntario, 1996

0

50,000

100,000

150,000

200,000

250,000

Hou

seho

lds

< $100

200-299

400-49

9

600-699

800-899

1000-1

099

1200-1

299

1400-1

499

1600-1

699

1800-1

899

2000-1

099

$2200

+

Rent

Source: Census and Ministry of Municipal Affairs and Housing.

It can be concluded from the above information that the non-profit housing program did not reduce the distribution of housing costs in Ontario. In fact, the average cost of housing produced under the program was well above average. This is demonstrated graphically to the right where the average monthly rent charged by non-profit housing providers is compared with the distribution of rents from the 1996 Census.

Non-Profit Housing Program Average Rent $1,127

The primary factor behind this is that the non-profit housing program was a new construction program. Throughout jurisdictions around the world, and throughout time, new construction is almost always more expensive than equivalent housing in the existing housing stock. That is because the newly constructed housing is not depreciated, and typically incorporates more modern design and building standards, all of which make it more costly, and more valuable. The program did face some criticisms with respect to the construction costs and operating costs under the program (Office of the Provincial Auditor, 1992). However, these criticisms notwithstanding, the primary reason the program was high in cost was because it was a new construction program.

The Income Mixing Premium Because the target group for affordable housing is core need households, the ultimate cost for the program should be calculated per core need household served. This is also necessary to compare the program to some of its alternatives, to allow an apples to apples comparison. This means the total of the market rent subsidies for the program must be


38

averaged into the cost per RGI household. If the program has a 25 percent market/75 percent RGI mix10, the average subsidy per RGI household increases by another $150 per month. This is the income mixing premium associated with the program. This brings the total cost per RGI household to $1,277 per month. If the market rent component of the program is higher (there were some projects in the program with as many as 75 percent market rent), the income mixing premium increases.

Non-Profit Housing, 1996

Average Rent - Household in

Core Need

New Construction

Premium

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

Source: FRPO.

Income Mixing Premium

Premium in Cost Associated with

Altogether then, using the conservative assumption of a 25 percent market component, the cost of housing a core need household in newly constructed non-profit housing was $664 more than giving them assistance to live in the existing stock, in which their average rent was $613 in 1996. The cost differential includes a new construction premium of $514 per household, and an income mixing premium of $150 per household.

Housing (Shelter) Allowances Housing allowances (also called shelter allowances) are increasingly being seen as the most effective and efficient government response to affordable housing concerns. Given our findings that housing affordability is primarily an income problem, this program response should be the primary strategy adopted by the government to address housing affordability problems. Luxton (1991) outlines a compelling case for New Zealand’s national housing allowance, which has since been a very successful program. Hills et al (1990) find that the housing allowance in Germany has been advantageous to the government, and that it has had minimal if any impact on rents. Numerous studies of the U.S. Experimental Housing Assistance Program (e.g. Bradbury and Downs, 1982; Freidman and Weinberg, 1983; and Lowry, 1982) found the large scale pilot program to be a tremendous success. All authors found conclusive evidence that the housing allowance did not result in rent inflation, and was very well received by the target households. Kain (1980) finds that “housing allowances or similar demand-side strategies are a far more cost-effective means of providing low income households with standard housing than the costly construction programs that federal policy has emphasized.” 10 According to the Office of the Provincial Auditor (1992), a sample of 30 projects found the proportion of RGI tenants varied from 62 percent in Central Ontario, to 77 percent in Southern Ontario, to 84 percent in Eastern Ontario.


39

Steele (1985a and 1985b) makes a compelling case for housing allowance programs nationally and for Ontario. British Columbia and Manitoba currently have targeted housing allowance programs, while Quebec has been the only province to create a universal entitlement program. However, it cannot be overemphasized that housing allowances need not be a universal entitlement program. Steele (2002) finds that Quebec’s universal housing allowance did not have a significant impact on rents or vacancy rates. Some considerations with respect to the implementation of housing allowances are outlined below.

Cost of a Housing Allowance Program As we have seen above, 1996 the average Core Need renter was spending $613 per month on rent. Their housing was typically suitable and adequate, but they could not afford to pay $613. The most they could afford to pay was $430. This means that an average subsidy of $183 per month would eliminate the housing affordability problem of the typical core need household. As noted above, the subsidy required to house the same typical core need household the non-profit housing program would have been $664 higher, for a total monthly cost of $847. In addition to this, a properly designed shelter allowance normally funds a percentage of the gap between 30 percent of income and rent. There is a good rationale for funding a percentage of the gap, which will be discussed later in this paper. This is how the Quebec Allocation Logement program is designed (see Steele, 2002). It is also how the New Zealand Accommodation Supplement is designed (see Luxton, 1991). This would mean that the average cost of the allowance would be even lower than $183 in 1996 if such design element were introduced. If the percentage of the gap subsidized was two thirds, as in Quebec, the average subsidy required per household would decline to $122. Other design elements of a shelter allowance could lower the average cost per household. For example, setting a ceiling on the eligible rent (and therefore subsidy) would lower the average cost per household further, by eliminating overly costly rentals, or over-housing. Clayton Research Associates (1993) found that this reduced the average subsidy requirements per household by 28 percent. This would reduce the subsidy required per household to about $100 per month. Steele (2002) finds that the average allowance in Quebec in 1998 was $65 per household with similar design parameters to those noted above, confirming that the cost per month in practice can be relatively low. There are a variety of other potential design elements in a shelter allowance program which may impact on costs.

Monthly Cost of Helping a Core Need Household With a Shelter Allowance vs.

Non-Profit Housing, 1996

100

847

$0

$200

$400

$600

$800

$1,000

Shelter Allowance Non-Profit Housing Subsidy


40

From an equity perspective, this means that for any given level of program funding, the government could help on average 8.5 core need households with a shelter allowance for every core need household helped through a new construction program. Far fewer households can be helped by the government through a new construction program. 1996 data was used above to allow a comparison of the cost of a shelter allowance to a new construction program. The 2001 core need data shows that the average rent of a core need household in Ontario was $708, but that the rent they could afford with an average income of $19,682 based on a 30 percent threshold was $492. Core need household incomes increased by about 14 percent between 1996 and 2001, while rents increased by about 15 percent. Therefore, a rough estimate of current costs could be had by inflating the cost estimates for 1996 above by 15 percent.

Design Considerations for a Shelter Allowance Design considerations are a critical part of a successful shelter allowance program. Steele (2002) finds that the general design of the Quebec housing allowances has advantages when compared to the housing voucher system used in the U.S. Percentage of the Gap Traditional RGI subsidies in Canada fund 100 percent of the difference between 30 percent of a tenant’s income and the market rent (or the cost of the housing, in the case of social housing). However, most policy papers on housing allowances suggest that the allowance fund a percentage of the gap, as is done in New Zealand (70%) and Quebec (66%) and Manitoba (90%). There are two benefits from incorporating this design element: • Incentive to economise: by funding a percentage of the gap, households have a

built- in incentive to economise on housing costs. Any increase in housing costs results in out of pocket costs for the household. Without such a design element, households participating in the program will have a greater incentive to increase their housing consumption up to the maximum limits of the program.

• Labour force attachment: if the government funds 100 percent of the gap, then any increase in household income is effectively taxed (clawed back) at 30 percent. If the government were to fund 75 percent of the gap, the marginal tax rate would fall to 22.5 percent.11

Portability The greatest advantage of housing allowances is their portability. The portability of the allowance provides for a number of benefits: 11 For example, suppose a household has an income of $12,000, and a rent of $700. An RGI subsidy would be $400 per month, and a 75% gap subsidy would be $300 per month. If the household’s income increases to $15,000, the RGI subsidy would decrease (be clawed back) by $75, an effective tax back rate of 30%, while the 75% gap subsidy would decline by $56, an effective tax back rate of 22.5 percent.


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• Recipient autonomy and satisfaction: a portable housing allowance lets the

household choose where they would like to live. This can only improve household satisfaction. Gallant et al (2004) find that the ability of tenants to move in Toronto’s recent portable subsidy pilot resulted in an increase in their level of satisfaction with their neighbourhood.

• Privacy: a housing allowance can be designed to go directly to the recipient, without a landlord’s knowledge. This means that landlords will not know that a tenant is receiving a subsidy. Steele (2002) reports on a study in Manitoba that shows landlords are generally unaware their tenants are receiving a shelter allowance. This has several benefits, including the following:

o Tenants will not face bias against program participants when making an initial application for a rental unit;

o Landlord-tenant negotiations will not be influenced by landlord awareness of program design;

o Tenants will have greater privacy, because they are not required to disclose their participation in the program to their landlord.

• Labour force attachment: currently, a household receiving traditional RGI assistance (public housing, non-profit housing or rent supplements) may lose their subsidy if they move. This may be a disincentive changing jobs, as a household may chose not to take any new job that required moving. This is not a problem for a portable shelter allowance.

• Ease of absorption: depending upon market conditions, landlords may be more or less receptive to participation in a traditional rent supplement program. This problem does not occur with a portable housing allowance, as landlords need not be involved in program participation.

Eligibility A shelter allowance can be targeted to any group, or made universally eligible, depending upon available funding. Quebec has made their allowance universally eligible to all families, including homeowners and welfare recipients. It can also be used to help transition households from welfare to the workforce. This approach maximizes equity, a longstanding problem with Canadian housing programs. B.C. limits their allowance to seniors, allowing the province to contain costs and target a specific group. Allowances can also be rationed in the same way social housing units are rationed to households on prioritized waiting lists. Steele (2002) finds that homeowner participation in the Quebec program is low, particularly amongst seniors, but high rates of participation amongst eligible single-parent and two-parent families. Regional Variation A shelter allowance can be designed to recognize regional variation in housing costs. For example, New Zealand varies is housing allowance depending upon which region of the


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country a recipient lives. Such a design element recognizes that there are significant differences in housing costs by region. Minimum Standards Some demand side programs have minimum standards, out of a public desire to ensure a minimum level of housing consumption of recipients. However, practical experience with other programs suggests that these may be more trouble than they are worth. They add a significant design complexity to a housing allowance program. Administrative costs are increased, as site inspections would be necessary for enforcement. There does not seem to be a good case for such standards. Individual households are best able to decide what level of housing consumption suits them best, and where they would like to live. While ceilings to prevent over-consumption make sense, because over-consumption increases program costs, the government does not need to treat program participants any differently than anyone else in Ontario who is not a program participant. Individuals and households are best able to choose the housing conditions that best suit them. If the program funding would allow a participant to move to a supposedly higher quality housing unit, because their individual subsidy would increase, but that household chooses not to move, it should be their decision and that decision should be respected.

Rent Supplements Rent supplements have been more commonplace as a demand side subsidy in Canada. Ontario currently has a number of rent supplement allocations across the province. Rent supplements do not have many of the advantages of a shelter allowance, because they are a contract with a specific landlord, not with the tenant. Therefore ,the advantages of a housing allowance which stem from its portability do not accrue to a rent supplement. However, they can have an advantage over new construction programs to the extent that they make use of the existing housing stock, which is older and less costly than new construction. They can also be converted over time into portable housing allowances. Rent supplements have the advantage currently of having a program infrastructure in place in Ontario. Therefore, in the short term the government may want to allocate funding into rent supplements, until such time as it can put in place the infrastructure for a housing allowance.

Immigration Support One of the key factors behind deteriorating incomes has been the changing earnings performance of recent immigrants to Canada. While it is beyond the scope of this paper to suggest assistance programs for immigrants, it would seem plausible given our findings that support programs for recent immigrants may be beneficial in addressing the


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growing earnings gap between recent immigrants and native-born Canadians. This might include government assistance in gaining recognition and acceptance of foreign work experience, as this has been identified as a key factor in the deterioration of immigrant earnings. Another possible avenue might be an enhancement to English as a second language training, as language difficulties have also been identified by the research as a possible causal factor in the deterioration of immigrant earnings.

Special Needs Housing While the bulk of the housing affordability problem is simply an income problem in Ontario, there are certain households who require housing that is specifically designed to meet their needs (e.g. modified for disabled access). In this case, a specific government program may be needed to modify the existing housing stock to make the housing meet the needs of these households, or to build new housing. This is necessary because the private market is not likely to provide this housing without some incentives. The amount of funding directed towards physical production of this housing should be based on a thorough needs assessment across the province. This assessment should examine the relative merits of providing incentives for the modification of existing buildings versus new construction, and at incentives for both private and non-profit housing providers to produce the housing. In some cases, it may be more cost effective to locate support services on a particular site, rather than to try to provide the support services separately. To the extent that this requires specific design elements, it may be cost-effective to build new housing in this circumstance.

Reductions In Government Barriers To Supply As we found from our research, next to providing income supports to address housing affordability, reducing barriers to the supply of housing is the most important thing that a government can do. Therefore, the direction the government takes following its “Places to Grow” consultation, and its plan for growth in the Greater Golden Horseshoe area, may have the largest impact on housing affordability in Ontario in the future. In some respects, the government’s goals in the area of curbing sprawl may be in conflict with its affordable housing goals. To the extent that policies brought in to curb sprawl result in a reduction in the supply of land zoned for residential, they will make housing less affordable for low income households. This effect can be mitigated in two ways:

1) Increase the allowable density of land brought forward for development; and 2) Make it easier to intensify already built-up areas.

The challenge with the first avenue for mitigation may be the ability of builders and developers to market higher density developments to consumers when they are located in suburban areas. The challenge with the second avenue of mitigation is that


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neighbourhood opposition to intensification is growing in Ontario, making such strategies politically unpopular. Therefore, there is a very strong provincial role in ensuring that neighbourhood opposition to new development does not overrun provincial objectives in the area of affordable housing, more efficient use of public infrastructure, and preservation of environmentally sensitive areas. This paper will not undertake an exhaustive analysis of land development and housing supply issues. However, our findings suggest the following general policy directions:

1) Strong Provincial Policy Statements: the province must provide clear direction to municipalities to ensure an adequate supply of land be made available for development. This should mean expanding the number of years of available land supply, closer provincial monitoring of municipal performance in meeting targets, and incentives for municipalities that meet or exceed targets.

2) A Strong Ontario Municipal Board (OMB) With a Clear Mandate: the

province needs to ensure that the OMB has the ability to overturn local decisions to prevent development based on NIMBY reaction. Many academics examining the problems created in U.S. housing markets by exclusionary zoning have called for state intervention to overcome local opposition to development, or for the creation of a body similar to the OMB. What is in the local interest (or the perceived local interest) is not necessarily in the provincial interest. If we reach a situation in Ontario where local opposition to development grows any further, every neighbourhood will resist development and suggest that the development go elsewhere. No one locality will then see its interest in allowing development to proceed. We are fortunate in Ontario to have an institution which can review local decisions against the provincial interest, namely the OMB.

3) More Provincial Intervention: the province should intervene at the OMB when

development applications are being opposed by municipalities, to ensure that the provincial interest in ensuring an adequate supply of housing is met.

4) Eliminate Rent Controls: rent controls have been shown conclusively to reduce

housing supply, while increasing demand, which worsens the housing affordability problem for low income households. With high vacancy rates in Ontario, this is an opportune time to eliminate them.

5) Demolition and Redevelopment: municipalities are currently preventing the

demolition, redevelopment and intensification of old rental buildings. The province should eliminate this barrier to new supply.

Property Tax Reform The multi-residential property tax in Ontario’s largest centres constitutes the most regressive tax in Canada. It drives up the cost of the housing where the lowest income


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people in our society live, but as much as $100 per month. This discriminatory tax is not justifiable. Therefore, the province should mandate that municipalities begin moving towards equalization immediately. This one reform has the potential to reduce or eliminate the housing affordability problem of tens of thousands of low income renters in the province.

Affordability Indicators and Thresholds One of the things that stands out in reviewing housing affordability conditions in Ontario is the inadequacy of current housing affordability indicators commonly used in Canada. It appears that housing affordability has actually been improving at the same time that our current affordability indicators suggest it is getting worse. Some of the inadequacies with current indicators are discussed briefly discussed below.

Replace Fixed Threshold STIRs With Variable STIRs The use of a fixed shelter (cost)-to-income ratio (STIR) of 30 percent does not seem appropriate or fair as a determinant of need. The per-capita non-shelter discretionary income available to a single person with an income of $15,000 and annual housing cost of $9,000 is $6,000. By contrast, a single parent with four children with the same income and shelter cost has a per capita non-shelter discretionary income of $1,500. Shelter to income thresholds should be varied by household type.

Replace Tenant STIRs with Household STIRs or Quintile STIRs Affordability should not be measured by comparing rents against tenant incomes, because tenant incomes are a residual in the distribution of overall household income. Using tenant income alone fails to account for the fact that income improvements result in tenants leaving for homeownership, and being replaced by even lower income tenants. This is because the tenants who form new households have low incomes and are at the margins of being able to form a household. Tenant household income affordability indicators give a false indication of affordability trends, because they fail to account for improving affordability.

Account for Household Formation and Changing Household Types This paper demonstrated that current affordability indicators measure improving social conditions as deteriorating housing affordability. This is because housing is a strongly desired commodity, and as incomes grow, more people and families become capable of sustaining an independent household. When they do so, they are recorded by current affordability measures as having an affordability problem. A simple way to mitigate this problem is to move to the use of per-capita income in measuring affordability. A per capita STIR would also more fairly reflect the non-housing discretionary income needs of different household types correcting the problem noted above. Altogether then, the above suggests that the current practice of measuring affordability through tenant household STIRs provides a misleading indication of affordability trends.


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This indicator should be replaced by an average rent to average per capita income indicator, which would partially address some of the issues identified above.


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Green, R. K. (1999). Land use regulation and the price of housing in a suburban Wisconsin County. Journal of Housing Economics, 8, 144-159. Green, R. K., Malpezzi S., & Mayo, S. K. (1999). Metropolitan specific estimates of the price elasticity of supply of housing, and their sources. Center for Urban Land Economics Research Working Paper. Madison, WI: University of Wisconsin, Madison. Goy, R. and M. Steele (1994). Alternative constant - quality price indexes for modest houses and condominiums in Kitchener Waterloo, Richard Goy Consulting, Guelph and department of economics, University of Guelph. Hills, J., Hubert, F., Tomann, H. and Whitehead, C. (1990). Shifting Subsidy from Bricks and Mortar to People: Experiences in Britain and West Germany, Housing Studies, Volume 5 Number 3, pp 147-167. Hosios, Arthur J. and Pesando, James E. (1991). Measuring Prices in Resale Housing Markets in Canada: Evidence and Implications, Journal of Housing Economics, Vol. 1, No. 4: 303-317. Hoyt, H., (1939). Housing Markets and Public Policy, Philadelphia: University of Pennsylvania Press. Kain, John F. (1980). Analysis of a Universal Housing Allowance Program. Department of City and Regional Planning, Harvard University. Kristof, Frank S (1965). Housing Policy Goals and the Turnover of Housing, Journal of the American Institute of Planners, August, 31: 232-245 Lansing, J., C. Clifton and J. Morgan (1969). New Homes and Poor People: A Study of Chains of Moves, University of Michigan Institute for Social Science Research, Ann Arbour Lefebvre, Sophie (2002). Housing: An income issue, Perspectives on labour and income, Statistics Canada, Vol. 3, no. 6. Levine, N. (1999). The effect of local growth controls on regional housing production and population redistribution in California. Urban Studies, 36, 2047-2068. Lindbeck, Assar (1971). The Political Economy of the New Left: An Outsider’s View (New York: Harper and Row, 1971). Lowry, Ira S. (1982). Experimenting with Housing Allowances, The Final Comprehensive Report of the Housing Assistance Supply Experiment, Office of Policy Development and Research, U.S. Department of Housing and Urban Development.


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Luxton, Hon. John (1991). Housing and Accommodation: Accommodation Assistance, A Statement of Government Policy on Housing and Accommodation, Wellington: New Zealand. Malpezzi, Stephen (1996). Housing Prices, Externalities, and Regulation in U.S. Metropolitan Areas. Journal of Housing Research 7(2):209–41. Malpezzi, S. & Green, R. K. (1996). What has happened to the bottom of the U.S. housing market? Urban Studies, 33, 1807-1820. Marks, Denton (1984). Housing Affordability and Rent Regulation, Research Study No. 8, Commission of Inquiry into Residential Tenancies. Marullo, S. (1985). Housing opportunities and vacancy chains, Urban Affairs Quarterly, 20, pp. 364-388. Mayer, C. J. & Somerville, C. T. (2000). Land use regulation and new construction. Regional Science and Urban Economics, 30, 639-662. Metro Planning (1996). Housing Patterns and Prospects, Metropolitan Toronto Planning Department, Municipality of Metropolitan Toronto. Miron, J. R. (1989). Household Formation, Affordability and Housing Policy, Population Research and Policy Review, Vol 8, No. 1: 55-77. Morisette, R. (1995). Why has Inequality in Weekly Earnings Increased in Canada?, Statistics Canada. Morisette, R. and Bérubé, C. (1996). Longitudinal Aspects of Earnings Inequality in Canada, Statistics Canada. Ontario Ministry of Finance (2003). Census 2001 Highlights, Queen’s Printer for Ontario. Picout, G. and Hou, F. (2003). The rise in low-income rates among immigrants in Canada, Statistics Canada. Pollakowski, H. O. & Wachter, S. M. (1990). The effects of land-use constraints on housing prices. Land Economics, 66, 315-324. Quigley, J.M. and Raphael, S. (2004). Is Housing Unaffordable? Why Isn’t It More Affordable, Journal of Economic Perspectives, Volume 18, Number 1: 191-214. Randolph, William C. (1988), “Housing Depreciation and Aging Bias in the Consumer Price Index,” Journal of Business and Economic Statistics, 6: 359-371.


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Ratcliff, Richard U. (1949). Urban Land Economics, McGraw Hill, New York. Region of Peel (1985). An affordable Rental Housing Strategy, Submission to the Commission of Inquiry into Residential Tenancies. Rydenfelt, Sven (1975). “The Rise and Fall of Swedish Rent Control”, Rent Control: A Popular Paradox, ed. F.A. Hayek, Canada: The Fraser Institute. Sands, Gary (1971) Housing Turnover and Filtering, Detroit: Mayor’s Committee for Community Renewal, Research Report, No. 8. Sands, G. and Bower, L. (1974). Vacancy Chains in the Local Housing Market, N. Y.: Center for Urban Development Research, Cornell University Sands, G. and Bower, L. (1976). Housing Turnover and Housing Policy: Case Studies of Vacancy Chains in New York State, Praeger Publishers, New York Sands, G. (1977), A Vacancy Transfer Model of the Structure of the Local Housing Market, American Real Estate and Urban Economics Association Journal, Vol. 5, 128-138 Shellenberg, Grant (2004). Immigrants in Canada's Census Metropolitan Areas, Statistics Canada. Smith, Wallace F (1964). Filtering and Neighborhood Change, Research Report No. 24, Center for Real Estate and Urban Economics, Institute of Urban and Regional Development, University of Carolina Stanbury, William T. and Vertinsky, I.B. (1986). Rent Regulation: Design Characteristics and Effects, Toronto: Commission of Inquiry Into Residential Tenancies. Statistics Canada (2002). Analysis of Income in Canada, Catalogue no. 75-203-XIE. Statistics Canada (2003). Longitudinal Survey of Immigrants to Canada: Process, progress and prospects, Housing, Family and Social Statistics Division. Steele, Marion and Miron, John (1984). Rent Regulation, Housing Affordability Problems, and Market Imperfections, Research Study No. 9 Toronto: Commission of Inquiry into Residential Tenancies. Steele, Marion (1985a). Canadian Housing Allowances: An Economic Analysis, Toronto: Ontario Economic Council. Steele, Marion (1985b). Housing Allowances: An Assessment of the Proposal for a National Program for Canada, Department of Economics, Guelph.


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APPENDIX A: IMMIGRATION TO ONTARIO REFLECTS NATIONAL TREND The Toronto CMA is the target destination for 47 percent of Canada’s immigrants, and Ontario absorbs about 59 percent of Canada’s immigrants. Therefore, it is not surprising to find that the immigration patterns nationally are also found in Ontario. As the table opposite shows, European immigrants accounted for 92.7 percent of the immigrants who came to Ontario before 1961. The United Kingdom, Italy, Germany and the Netherlands accounted for 64% of all immigrants to Ontario before 1961. By the 1990s, these countries accounted for just 3.1% of immigrants. Conversely, immigration from China has grown steadily, accounting for 16 percent of all immigrants who came to Ontario in the past decade, followed by India (9%), the Philippines (6%), Sri Lanka (5.2%) and Pakistan (4.5%).12 Therefore, research on income distribution patterns for new immigrants to Canada are applicable to Ontario.

Place of Birth Immigrants to Ontario (%) Before

1961 1991-2001

Asia 2.3 58.1 Europe 92.7 20.2 Americas 4.4 14.6 Africa 0.4 6.8 Oceania 0.2 0.3 Other 0.1 6 Total 100 100 Source: Ont. Ministry of Finance, based on 2001 Census

Population Comprised of Recent Immigrants (%)

(Settled in Last 10 Years) CMA 1981 1991 Toronto 13.2 17.3 Windsor 4.9 8.0 Ottawa-Hull 4.2 6.8 Kitchener 6.7 6.4 Hamilton 5.1 5.5 London 4.6 4.6 Source: Shellenberg (2003)

As the table to the right shows, recent immigrants constitute a growing portion of the population of Ontario’s two largest CMA’s, Toronto and Ottawa, and for Windsor. Not only has the income of immigrants been declining, they account for a growing portion of the population of Ontario, particularly in the larger centres. Altogether, we can see that changing earnings for recent immigrations explains a significant portion of the changing income distribution in Ontario. The percentage of recent immigrants (past ten years) who are renters varies from 57 percent in Toronto to 70 percent in Ottawa-Hull. Recent immigrants are much more likely to be renters than native born Canadians. This means that declining incomes for immigrants will have a much greater impact on rent to income statistics for renters than it will for homeowners.

Percent of Recent Immigrants Who are Renters, 2001

0

10

2030

40

50

60

7080

TorontoWindsor

Ottawa-Hull

KitchenerHamilton

London

Source: Shellenberg (2004).

Twelve percent of immigrants who landed in 2001 lived in multiple-family households, compared to two percent for the total Canadian population. Consequently, the average household size for these recent immigrants was 3.5 people, compared to 2.6 for Canada (Statistics Canada, 2003). This might be expected given their lower average incomes. 12 Country specific immigration percentages are from Ontario Ministry of Finance (2003).


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